תזמון עובדים

ארגונים שהעובדים שלהם עובדים כמה משמרות צריכים לקבוע לוח זמנים מתאים עובדים בכל משמרת יומית. בדרך כלל, לוחות הזמנים יכללו מגבלות, למשל: "אף עובד לא צריך לעבוד שתי משמרות ברצף". איתור לוח זמנים שעומד בכל המגבלות, יכול להיות קשה מבחינה חישובית.

בקטעים הבאים מוצגות שתי דוגמאות לבעיות של תזמון עובדים, מראים איך לפתור אותן באמצעות פותר הבעיות שקשורות ל-CP-SAT.

דוגמה מתוחכמת יותר מופיעה כאן: תוכנית לתזמון שינוי ב-GitHub.

מחקר התפעול של Google ה-API מספק תזמון כוח עבודה בחינם לפתרון בעיות נפוצות רבות.

בעיה בלוח הזמנים של אחות

בדוגמה הבאה, מנהל בית חולים צריך ליצור לוח זמנים עבור ארבעה אחיות במשך שלושה ימים, בכפוף לתנאים הבאים:

• כל יום מחולק לשלוש משמרות של 8 שעות.
• בכל יום, כל משמרת מוקצית לאחות אחת, ואף אח או אחות לא עובדים יותר
• כל אחות מוקצית לשתי משמרות לפחות במהלך התקופה של שלושת הימים.

בקטעים הבאים מוצג פתרון לבעיית התזמון של האחות.

ייבוא הספריות

הקוד הבא מייבא את הספרייה הנדרשת.

Python

from ortools.sat.python import cp_model

C++‎

#include <stdlib.h>

#include <atomic>
#include <map>
#include <numeric>
#include <string>
#include <tuple>
#include <vector>

#include "absl/strings/str_format.h"
#include "ortools/base/logging.h"
#include "ortools/sat/cp_model.h"
#include "ortools/sat/cp_model.pb.h"
#include "ortools/sat/cp_model_solver.h"
#include "ortools/sat/model.h"
#include "ortools/sat/sat_parameters.pb.h"
#include "ortools/util/time_limit.h"

Java

import com.google.ortools.Loader;
import com.google.ortools.sat.CpModel;
import com.google.ortools.sat.CpSolver;
import com.google.ortools.sat.CpSolverSolutionCallback;
import com.google.ortools.sat.CpSolverStatus;
import com.google.ortools.sat.LinearExpr;
import com.google.ortools.sat.LinearExprBuilder;
import com.google.ortools.sat.Literal;
import java.util.ArrayList;
import java.util.List;
import java.util.stream.IntStream;

C#‎

using System;
using System.Collections.Generic;
using System.IO;
using System.Linq;
using Google.OrTools.Sat;

נתונים עבור הדוגמה

הקוד הבא יוצר את הנתונים בשביל הדוגמה.

Python

num_nurses = 4
num_shifts = 3
num_days = 3
all_nurses = range(num_nurses)
all_shifts = range(num_shifts)
all_days = range(num_days)

C++‎

const int num_nurses = 4;
const int num_shifts = 3;
const int num_days = 3;

std::vector<int> all_nurses(num_nurses);
std::iota(all_nurses.begin(), all_nurses.end(), 0);

std::vector<int> all_shifts(num_shifts);
std::iota(all_shifts.begin(), all_shifts.end(), 0);

std::vector<int> all_days(num_days);
std::iota(all_days.begin(), all_days.end(), 0);

Java

final int numNurses = 4;
final int numDays = 3;
final int numShifts = 3;

final int[] allNurses = IntStream.range(0, numNurses).toArray();
final int[] allDays = IntStream.range(0, numDays).toArray();
final int[] allShifts = IntStream.range(0, numShifts).toArray();

C#‎

const int numNurses = 4;
const int numDays = 3;
const int numShifts = 3;

int[] allNurses = Enumerable.Range(0, numNurses).ToArray();
int[] allDays = Enumerable.Range(0, numDays).ToArray();
int[] allShifts = Enumerable.Range(0, numShifts).ToArray();

יצירת המודל

הקוד הבא יוצר את המודל.

Python

model = cp_model.CpModel()

C++‎

CpModelBuilder cp_model;

Java

CpModel model = new CpModel();

C#‎

CpModel model = new CpModel();
model.Model.Variables.Capacity = numNurses * numDays * numShifts;

יצירת המשתנים

הקוד הבא יוצר מערך של משתנים.

Python

shifts = {}
for n in all_nurses:
    for d in all_days:
        for s in all_shifts:
            shifts[(n, d, s)] = model.new_bool_var(f"shift_n{n}_d{d}_s{s}")

C++‎

std::map<std::tuple<int, int, int>, BoolVar> shifts;
for (int n : all_nurses) {
  for (int d : all_days) {
    for (int s : all_shifts) {
      auto key = std::make_tuple(n, d, s);
      shifts[key] = cp_model.NewBoolVar().WithName(
          absl::StrFormat("shift_n%dd%ds%d", n, d, s));
    }
  }
}

Java

Literal[][][] shifts = new Literal[numNurses][numDays][numShifts];
for (int n : allNurses) {
  for (int d : allDays) {
    for (int s : allShifts) {
      shifts[n][d][s] = model.newBoolVar("shifts_n" + n + "d" + d + "s" + s);
    }
  }
}

C#‎

Dictionary<(int, int, int), BoolVar> shifts =
    new Dictionary<(int, int, int), BoolVar>(numNurses * numDays * numShifts);
foreach (int n in allNurses)
{
    foreach (int d in allDays)
    {
        foreach (int s in allShifts)
        {
            shifts.Add((n, d, s), model.NewBoolVar($"shifts_n{n}d{d}s{s}"));
        }
    }
}

המערך מגדיר הקצאות למשמרות לאחיות באופן הבא: shifts[(n, d, s)] שווה ל-1 אם המשמרת s מוקצית לאחות n ביום d, ו-0 אחרת.

הקצאת אחיות למשמרות

בשלב הבא נראה איך להקצות אחים למשמרות בכפוף למגבלות הבאות:

• כל משמרת מוקצית לאחות אחת ביום.
• כל אחים עובדים במשמרת אחת לכל היותר ביום.

זה הקוד שיוצר את התנאי הראשון.

Python

for d in all_days:
    for s in all_shifts:
        model.add_exactly_one(shifts[(n, d, s)] for n in all_nurses)

C++‎

for (int d : all_days) {
  for (int s : all_shifts) {
    std::vector<BoolVar> nurses;
    for (int n : all_nurses) {
      auto key = std::make_tuple(n, d, s);
      nurses.push_back(shifts[key]);
    }
    cp_model.AddExactlyOne(nurses);
  }
}

Java

for (int d : allDays) {
  for (int s : allShifts) {
    List<Literal> nurses = new ArrayList<>();
    for (int n : allNurses) {
      nurses.add(shifts[n][d][s]);
    }
    model.addExactlyOne(nurses);
  }
}

C#‎

List<ILiteral> literals = new List<ILiteral>();
foreach (int d in allDays)
{
    foreach (int s in allShifts)
    {
        foreach (int n in allNurses)
        {
            literals.Add(shifts[(n, d, s)]);
        }
        model.AddExactlyOne(literals);
        literals.Clear();
    }
}

בשורה האחרונה כתוב שלכל משמרת סכום האחיות שהוקצו Shift הוא 1.

בהמשך, זה הקוד שדורש שכל אחות תעבוד לכל היותר במשמרת אחת יום.

Python

for n in all_nurses:
    for d in all_days:
        model.add_at_most_one(shifts[(n, d, s)] for s in all_shifts)

C++‎

for (int n : all_nurses) {
  for (int d : all_days) {
    std::vector<BoolVar> work;
    for (int s : all_shifts) {
      auto key = std::make_tuple(n, d, s);
      work.push_back(shifts[key]);
    }
    cp_model.AddAtMostOne(work);
  }
}

Java

for (int n : allNurses) {
  for (int d : allDays) {
    List<Literal> work = new ArrayList<>();
    for (int s : allShifts) {
      work.add(shifts[n][d][s]);
    }
    model.addAtMostOne(work);
  }
}

C#‎

foreach (int n in allNurses)
{
    foreach (int d in allDays)
    {
        foreach (int s in allShifts)
        {
            literals.Add(shifts[(n, d, s)]);
        }
        model.AddAtMostOne(literals);
        literals.Clear();
    }
}

עבור כל אחות, סכום המשמרות שהוקצו לאותה אחות הוא 1 לכל היותר ('לכל היותר' כי אחות עשויה לקבל יום חופש).

הקצאת משמרות באופן שווה

בשלב הבא נראה איך להקצות משמרות לאחיות באופן שווה ככל האפשר. מכיוון שיש תשע התאמות במהלך שלושת הימים, נוכל להקצות שתי משמרות לכל אחת מארבע האחיות. לאחר מכן תהיה משמרת אחת ואפשר להקצות אותה לכל אח.

הקוד הבא מבטיח שכל אחות עובדת לפחות שתי משמרות בתקופה של שלושה ימים.

Python

# Try to distribute the shifts evenly, so that each nurse works
# min_shifts_per_nurse shifts. If this is not possible, because the total
# number of shifts is not divisible by the number of nurses, some nurses will
# be assigned one more shift.
min_shifts_per_nurse = (num_shifts * num_days) // num_nurses
if num_shifts * num_days % num_nurses == 0:
    max_shifts_per_nurse = min_shifts_per_nurse
else:
    max_shifts_per_nurse = min_shifts_per_nurse + 1
for n in all_nurses:
    shifts_worked = []
    for d in all_days:
        for s in all_shifts:
            shifts_worked.append(shifts[(n, d, s)])
    model.add(min_shifts_per_nurse <= sum(shifts_worked))
    model.add(sum(shifts_worked) <= max_shifts_per_nurse)

C++‎

// Try to distribute the shifts evenly, so that each nurse works
// min_shifts_per_nurse shifts. If this is not possible, because the total
// number of shifts is not divisible by the number of nurses, some nurses will
// be assigned one more shift.
int min_shifts_per_nurse = (num_shifts * num_days) / num_nurses;
int max_shifts_per_nurse;
if ((num_shifts * num_days) % num_nurses == 0) {
  max_shifts_per_nurse = min_shifts_per_nurse;
} else {
  max_shifts_per_nurse = min_shifts_per_nurse + 1;
}
for (int n : all_nurses) {
  std::vector<BoolVar> shifts_worked;
  for (int d : all_days) {
    for (int s : all_shifts) {
      auto key = std::make_tuple(n, d, s);
      shifts_worked.push_back(shifts[key]);
    }
  }
  cp_model.AddLessOrEqual(min_shifts_per_nurse,
                          LinearExpr::Sum(shifts_worked));
  cp_model.AddLessOrEqual(LinearExpr::Sum(shifts_worked),
                          max_shifts_per_nurse);
}

Java

// Try to distribute the shifts evenly, so that each nurse works
// minShiftsPerNurse shifts. If this is not possible, because the total
// number of shifts is not divisible by the number of nurses, some nurses will
// be assigned one more shift.
int minShiftsPerNurse = (numShifts * numDays) / numNurses;
int maxShiftsPerNurse;
if ((numShifts * numDays) % numNurses == 0) {
  maxShiftsPerNurse = minShiftsPerNurse;
} else {
  maxShiftsPerNurse = minShiftsPerNurse + 1;
}
for (int n : allNurses) {
  LinearExprBuilder shiftsWorked = LinearExpr.newBuilder();
  for (int d : allDays) {
    for (int s : allShifts) {
      shiftsWorked.add(shifts[n][d][s]);
    }
  }
  model.addLinearConstraint(shiftsWorked, minShiftsPerNurse, maxShiftsPerNurse);
}

C#‎

// Try to distribute the shifts evenly, so that each nurse works
// minShiftsPerNurse shifts. If this is not possible, because the total
// number of shifts is not divisible by the number of nurses, some nurses will
// be assigned one more shift.
int minShiftsPerNurse = (numShifts * numDays) / numNurses;
int maxShiftsPerNurse;
if ((numShifts * numDays) % numNurses == 0)
{
    maxShiftsPerNurse = minShiftsPerNurse;
}
else
{
    maxShiftsPerNurse = minShiftsPerNurse + 1;
}

List<IntVar> shiftsWorked = new List<IntVar>();
foreach (int n in allNurses)
{
    foreach (int d in allDays)
    {
        foreach (int s in allShifts)
        {
            shiftsWorked.Add(shifts[(n, d, s)]);
        }
    }
    model.AddLinearConstraint(LinearExpr.Sum(shiftsWorked), minShiftsPerNurse, maxShiftsPerNurse);
    shiftsWorked.Clear();
}

מכיוון שיש num_shifts * num_days התאמות בסך הכל בתקופת התזמון, יכול להקצות לפחות (num_shifts * num_days) // num_nurses

עובר לכל אחים, אבל יכול להיות שחלק מהשינויים יישארו. (כאן // הוא Python אופרטור חילוק של מספרים שלמים, שמחזיר את הסף של המנה הרגילה).

לערכים הנתונים של num_nurses = 4, num_shifts = 3 ו-num_days = 3, הביטוי min_shifts_per_nurse מכיל את הערך (3 * 3 // 4) = 2, כך שיכול להקצות לפחות שתי משמרות לכל אחות. מצוין על ידי אילוץ (כאן ב-Python)

model.add(min_shifts_per_nurse <= sum(shifts_worked))

מכיוון שיש תשע התאמות בסך הכל בתקופה של שלושת הימים, יש שינוי אחד למשמרת שנותרה אחרי הקצאת שתי משמרות לכל אחות. ההתאמה הנוספת יכולה להיות שהוקצו לכל אח ואחות.

השורה האחרונה (כאן ב-Python)

model.add(sum(shifts_worked) <= max_shifts_per_nurse)

מבטיח שלא תוקצה אף אח או אחות יותר ממשמרת אחת נוספת.

במקרה הזה אין צורך באילוץ, כי יש רק עוד אפשרות אחת מקש Shift. אבל לגבי ערכי פרמטרים שונים, יכולים להיות כמה שינויים נוספים, במקרה כזה האילוץ נחוץ.

עדכון הפרמטרים של פותר

במודל ללא אופטימיזציה, אפשר להפעיל את החיפוש עבור כל הפתרונות.

Python

solver = cp_model.CpSolver()
solver.parameters.linearization_level = 0
# Enumerate all solutions.
solver.parameters.enumerate_all_solutions = True

C++‎

Model model;
SatParameters parameters;
parameters.set_linearization_level(0);
// Enumerate all solutions.
parameters.set_enumerate_all_solutions(true);
model.Add(NewSatParameters(parameters));

Java

CpSolver solver = new CpSolver();
solver.getParameters().setLinearizationLevel(0);
// Tell the solver to enumerate all solutions.
solver.getParameters().setEnumerateAllSolutions(true);

C#‎

CpSolver solver = new CpSolver();
// Tell the solver to enumerate all solutions.
solver.StringParameters += "linearization_level:0 " + "enumerate_all_solutions:true ";

רישום קריאה חוזרת (callback) לפתרונות

עליך לרשום קריאה חוזרת (callback) לפותר שתיקשר בכל אחד לפתרון הבעיה.

Python

class NursesPartialSolutionPrinter(cp_model.CpSolverSolutionCallback):
    """Print intermediate solutions."""

    def __init__(self, shifts, num_nurses, num_days, num_shifts, limit):
        cp_model.CpSolverSolutionCallback.__init__(self)
        self._shifts = shifts
        self._num_nurses = num_nurses
        self._num_days = num_days
        self._num_shifts = num_shifts
        self._solution_count = 0
        self._solution_limit = limit

    def on_solution_callback(self):
        self._solution_count += 1
        print(f"Solution {self._solution_count}")
        for d in range(self._num_days):
            print(f"Day {d}")
            for n in range(self._num_nurses):
                is_working = False
                for s in range(self._num_shifts):
                    if self.value(self._shifts[(n, d, s)]):
                        is_working = True
                        print(f"  Nurse {n} works shift {s}")
                if not is_working:
                    print(f"  Nurse {n} does not work")
        if self._solution_count >= self._solution_limit:
            print(f"Stop search after {self._solution_limit} solutions")
            self.stop_search()

    def solutionCount(self):
        return self._solution_count

# Display the first five solutions.
solution_limit = 5
solution_printer = NursesPartialSolutionPrinter(
    shifts, num_nurses, num_days, num_shifts, solution_limit
)

C++‎

// Create an atomic Boolean that will be periodically checked by the limit.
std::atomic<bool> stopped(false);
model.GetOrCreate<TimeLimit>()->RegisterExternalBooleanAsLimit(&stopped);

const int kSolutionLimit = 5;
int num_solutions = 0;
model.Add(NewFeasibleSolutionObserver([&](const CpSolverResponse& r) {
  LOG(INFO) << "Solution " << num_solutions;
  for (int d : all_days) {
    LOG(INFO) << "Day " << std::to_string(d);
    for (int n : all_nurses) {
      bool is_working = false;
      for (int s : all_shifts) {
        auto key = std::make_tuple(n, d, s);
        if (SolutionIntegerValue(r, shifts[key])) {
          is_working = true;
          LOG(INFO) << "  Nurse " << std::to_string(n) << " works shift "
                    << std::to_string(s);
        }
      }
      if (!is_working) {
        LOG(INFO) << "  Nurse " << std::to_string(n) << " does not work";
      }
    }
  }
  num_solutions++;
  if (num_solutions >= kSolutionLimit) {
    stopped = true;
    LOG(INFO) << "Stop search after " << kSolutionLimit << " solutions.";
  }
}));

Java

final int solutionLimit = 5;
class VarArraySolutionPrinterWithLimit extends CpSolverSolutionCallback {
  public VarArraySolutionPrinterWithLimit(
      int[] allNurses, int[] allDays, int[] allShifts, Literal[][][] shifts, int limit) {
    solutionCount = 0;
    this.allNurses = allNurses;
    this.allDays = allDays;
    this.allShifts = allShifts;
    this.shifts = shifts;
    solutionLimit = limit;
  }

  @Override
  public void onSolutionCallback() {
    System.out.printf("Solution #%d:%n", solutionCount);
    for (int d : allDays) {
      System.out.printf("Day %d%n", d);
      for (int n : allNurses) {
        boolean isWorking = false;
        for (int s : allShifts) {
          if (booleanValue(shifts[n][d][s])) {
            isWorking = true;
            System.out.printf("  Nurse %d work shift %d%n", n, s);
          }
        }
        if (!isWorking) {
          System.out.printf("  Nurse %d does not work%n", n);
        }
      }
    }
    solutionCount++;
    if (solutionCount >= solutionLimit) {
      System.out.printf("Stop search after %d solutions%n", solutionLimit);
      stopSearch();
    }
  }

  public int getSolutionCount() {
    return solutionCount;
  }

  private int solutionCount;
  private final int[] allNurses;
  private final int[] allDays;
  private final int[] allShifts;
  private final Literal[][][] shifts;
  private final int solutionLimit;
}

VarArraySolutionPrinterWithLimit cb =
    new VarArraySolutionPrinterWithLimit(allNurses, allDays, allShifts, shifts, solutionLimit);

C#‎

קודם צריך להגדיר את המחלקה SolutionPrinter.

public class SolutionPrinter : CpSolverSolutionCallback
{
    public SolutionPrinter(int[] allNurses, int[] allDays, int[] allShifts,
                           Dictionary<(int, int, int), BoolVar> shifts, int limit)
    {
        solutionCount_ = 0;
        allNurses_ = allNurses;
        allDays_ = allDays;
        allShifts_ = allShifts;
        shifts_ = shifts;
        solutionLimit_ = limit;
    }

    public override void OnSolutionCallback()
    {
        Console.WriteLine($"Solution #{solutionCount_}:");
        foreach (int d in allDays_)
        {
            Console.WriteLine($"Day {d}");
            foreach (int n in allNurses_)
            {
                bool isWorking = false;
                foreach (int s in allShifts_)
                {
                    if (Value(shifts_[(n, d, s)]) == 1L)
                    {
                        isWorking = true;
                        Console.WriteLine($"  Nurse {n} work shift {s}");
                    }
                }
                if (!isWorking)
                {
                    Console.WriteLine($"  Nurse {d} does not work");
                }
            }
        }
        solutionCount_++;
        if (solutionCount_ >= solutionLimit_)
        {
            Console.WriteLine($"Stop search after {solutionLimit_} solutions");
            StopSearch();
        }
    }

    public int SolutionCount()
    {
        return solutionCount_;
    }

    private int solutionCount_;
    private int[] allNurses_;
    private int[] allDays_;
    private int[] allShifts_;
    private Dictionary<(int, int, int), BoolVar> shifts_;
    private int solutionLimit_;
}

ואז יוצרים ממנו מופע באמצעות:

const int solutionLimit = 5;
SolutionPrinter cb = new SolutionPrinter(allNurses, allDays, allShifts, shifts, solutionLimit);

הפעלת הפותר

הקוד הבא מפעיל את הפותר ומציג את חמשת הפתרונות הראשונים.

Python

solver.solve(model, solution_printer)

C++‎

const CpSolverResponse response = SolveCpModel(cp_model.Build(), &model);

Java

CpSolverStatus status = solver.solve(model, cb);
System.out.println("Status: " + status);
System.out.println(cb.getSolutionCount() + " solutions found.");

C#‎

CpSolverStatus status = solver.Solve(model, cb);
Console.WriteLine($"Solve status: {status}");

פתרונות

אלה חמשת הפתרונות הראשונים.

Solution 0
Day 0
Nurse 0 does not work
Nurse 1 works shift 0
Nurse 2 works shift 1
Nurse 3 works shift 2
Day 1
Nurse 0 works shift 2
Nurse 1 does not work
Nurse 2 works shift 1
Nurse 3 works shift 0
Day 2
Nurse 0 works shift 2
Nurse 1 works shift 1
Nurse 2 works shift 0
Nurse 3 does not work

Solution 1
Day 0
Nurse 0 works shift 0
Nurse 1 does not work
Nurse 2 works shift 1
Nurse 3 works shift 2
Day 1
Nurse 0 does not work
Nurse 1 works shift 2
Nurse 2 works shift 1
Nurse 3 works shift 0
Day 2
Nurse 0 works shift 2
Nurse 1 works shift 1
Nurse 2 works shift 0
Nurse 3 does not work

Solution 2
Day 0 Nurse 0 works shift 0
Nurse 1 does not work
Nurse 2 works shift 1
Nurse 3 works shift 2
Day 1
Nurse 0 works shift 1
Nurse 1 works shift 2
Nurse 2 does not work
Nurse 3 works shift 0
Day 2
Nurse 0 works shift 2
Nurse 1 works shift 1
Nurse 2 works shift 0
Nurse 3 does not work

Solution 3
Day 0 Nurse 0 does not work
Nurse 1 works shift 0
Nurse 2 works shift 1
Nurse 3 works shift 2
Day 1
Nurse 0 works shift 1
Nurse 1 works shift 2
Nurse 2 does not work
Nurse 3 works shift 0
Day 2
Nurse 0 works shift 2
Nurse 1 works shift 1
Nurse 2 works shift 0
Nurse 3 does not work

Solution 4
Day 0
Nurse 0 does not work
Nurse 1 works shift 0
Nurse 2 works shift 1
Nurse 3 works shift 2
Day 1
Nurse 0 works shift 2
Nurse 1 works shift 1
Nurse 2 does not work
Nurse 3 works shift 0
Day 2
Nurse 0 works shift 2
Nurse 1 works shift 1
Nurse 2 works shift 0
Nurse 3 does not work

Statistics
  - conflicts      : 5
  - branches       : 142
  - wall time      : 0.002484 s
  - solutions found: 5

מספר הפתרונות הכולל הוא 5184. ארגומנט הספירה הבא מסביר את הסיבה לכך.

קודם כול, יש 4 אפשרויות לבחור אחות אחת שעובדת משמרת נוספת. אחרי שבחרתם אחות, יש 3 משמרות שבהן אפשר להקצות לאחות כל אחד מ-3 הימים, אז את מספר הדרכים האפשריות להקצות לאחות ההתאמה הנוספת היא 4 · 3³ = 108. אחרי הקצאת האחות הזו, בכל יום נשארו שתי משמרות שלא הוקצו.

מתוך שלוש האחיות הנותרות, אחת עובדת ביום 0 ו-1, אחת עובדת בימים 0 ו-2, ואחד מהימים 1 ו-2 עובד. יש 3 אפשרויות! = 6 דרכים להקצות את האחיות בימים האלה, כמו שמוצג של התרשים שלמטה. (שלוש האחיות מסומנות א', ב' ו-ג', ועדיין לא הקצה אותם למשמרות.)

Day 0    Day 1    Day 2
 A B      A C      B C
 A B      B C      A C
 A C      A B      B C
 A C      B C      A B
 B C      A B      A C
 B C      A C      A B

בכל שורה בתרשים שלמעלה, יש 8² = 8 דרכים להקצות את שאר המשמרות לאחיות (שתי אפשרויות בכל יום). לכן, המספר הכולל של המטלות האפשריות הוא 5184 = 108·6·8.

כל התוכנית

כאן מוצגת התוכנית המלאה לטיפול בבעיה של לוח הזמנים האחיות.

Python

"""Example of a simple nurse scheduling problem."""
from ortools.sat.python import cp_model


def main() -> None:
    # Data.
    num_nurses = 4
    num_shifts = 3
    num_days = 3
    all_nurses = range(num_nurses)
    all_shifts = range(num_shifts)
    all_days = range(num_days)

    # Creates the model.
    model = cp_model.CpModel()

    # Creates shift variables.
    # shifts[(n, d, s)]: nurse 'n' works shift 's' on day 'd'.
    shifts = {}
    for n in all_nurses:
        for d in all_days:
            for s in all_shifts:
                shifts[(n, d, s)] = model.new_bool_var(f"shift_n{n}_d{d}_s{s}")

    # Each shift is assigned to exactly one nurse in the schedule period.
    for d in all_days:
        for s in all_shifts:
            model.add_exactly_one(shifts[(n, d, s)] for n in all_nurses)

    # Each nurse works at most one shift per day.
    for n in all_nurses:
        for d in all_days:
            model.add_at_most_one(shifts[(n, d, s)] for s in all_shifts)

    # Try to distribute the shifts evenly, so that each nurse works
    # min_shifts_per_nurse shifts. If this is not possible, because the total
    # number of shifts is not divisible by the number of nurses, some nurses will
    # be assigned one more shift.
    min_shifts_per_nurse = (num_shifts * num_days) // num_nurses
    if num_shifts * num_days % num_nurses == 0:
        max_shifts_per_nurse = min_shifts_per_nurse
    else:
        max_shifts_per_nurse = min_shifts_per_nurse + 1
    for n in all_nurses:
        shifts_worked = []
        for d in all_days:
            for s in all_shifts:
                shifts_worked.append(shifts[(n, d, s)])
        model.add(min_shifts_per_nurse <= sum(shifts_worked))
        model.add(sum(shifts_worked) <= max_shifts_per_nurse)

    # Creates the solver and solve.
    solver = cp_model.CpSolver()
    solver.parameters.linearization_level = 0
    # Enumerate all solutions.
    solver.parameters.enumerate_all_solutions = True

    class NursesPartialSolutionPrinter(cp_model.CpSolverSolutionCallback):
        """Print intermediate solutions."""

        def __init__(self, shifts, num_nurses, num_days, num_shifts, limit):
            cp_model.CpSolverSolutionCallback.__init__(self)
            self._shifts = shifts
            self._num_nurses = num_nurses
            self._num_days = num_days
            self._num_shifts = num_shifts
            self._solution_count = 0
            self._solution_limit = limit

        def on_solution_callback(self):
            self._solution_count += 1
            print(f"Solution {self._solution_count}")
            for d in range(self._num_days):
                print(f"Day {d}")
                for n in range(self._num_nurses):
                    is_working = False
                    for s in range(self._num_shifts):
                        if self.value(self._shifts[(n, d, s)]):
                            is_working = True
                            print(f"  Nurse {n} works shift {s}")
                    if not is_working:
                        print(f"  Nurse {n} does not work")
            if self._solution_count >= self._solution_limit:
                print(f"Stop search after {self._solution_limit} solutions")
                self.stop_search()

        def solutionCount(self):
            return self._solution_count

    # Display the first five solutions.
    solution_limit = 5
    solution_printer = NursesPartialSolutionPrinter(
        shifts, num_nurses, num_days, num_shifts, solution_limit
    )

    solver.solve(model, solution_printer)

    # Statistics.
    print("\nStatistics")
    print(f"  - conflicts      : {solver.num_conflicts}")
    print(f"  - branches       : {solver.num_branches}")
    print(f"  - wall time      : {solver.wall_time} s")
    print(f"  - solutions found: {solution_printer.solutionCount()}")


if __name__ == "__main__":
    main()

C++‎

// Example of a simple nurse scheduling problem.
#include <stdlib.h>

#include <atomic>
#include <map>
#include <numeric>
#include <string>
#include <tuple>
#include <vector>

#include "absl/strings/str_format.h"
#include "ortools/base/logging.h"
#include "ortools/sat/cp_model.h"
#include "ortools/sat/cp_model.pb.h"
#include "ortools/sat/cp_model_solver.h"
#include "ortools/sat/model.h"
#include "ortools/sat/sat_parameters.pb.h"
#include "ortools/util/time_limit.h"

namespace operations_research {
namespace sat {

void NurseSat() {
  const int num_nurses = 4;
  const int num_shifts = 3;
  const int num_days = 3;

  std::vector<int> all_nurses(num_nurses);
  std::iota(all_nurses.begin(), all_nurses.end(), 0);

  std::vector<int> all_shifts(num_shifts);
  std::iota(all_shifts.begin(), all_shifts.end(), 0);

  std::vector<int> all_days(num_days);
  std::iota(all_days.begin(), all_days.end(), 0);

  // Creates the model.
  CpModelBuilder cp_model;

  // Creates shift variables.
  // shifts[(n, d, s)]: nurse 'n' works shift 's' on day 'd'.
  std::map<std::tuple<int, int, int>, BoolVar> shifts;
  for (int n : all_nurses) {
    for (int d : all_days) {
      for (int s : all_shifts) {
        auto key = std::make_tuple(n, d, s);
        shifts[key] = cp_model.NewBoolVar().WithName(
            absl::StrFormat("shift_n%dd%ds%d", n, d, s));
      }
    }
  }

  // Each shift is assigned to exactly one nurse in the schedule period.
  for (int d : all_days) {
    for (int s : all_shifts) {
      std::vector<BoolVar> nurses;
      for (int n : all_nurses) {
        auto key = std::make_tuple(n, d, s);
        nurses.push_back(shifts[key]);
      }
      cp_model.AddExactlyOne(nurses);
    }
  }

  // Each nurse works at most one shift per day.
  for (int n : all_nurses) {
    for (int d : all_days) {
      std::vector<BoolVar> work;
      for (int s : all_shifts) {
        auto key = std::make_tuple(n, d, s);
        work.push_back(shifts[key]);
      }
      cp_model.AddAtMostOne(work);
    }
  }

  // Try to distribute the shifts evenly, so that each nurse works
  // min_shifts_per_nurse shifts. If this is not possible, because the total
  // number of shifts is not divisible by the number of nurses, some nurses will
  // be assigned one more shift.
  int min_shifts_per_nurse = (num_shifts * num_days) / num_nurses;
  int max_shifts_per_nurse;
  if ((num_shifts * num_days) % num_nurses == 0) {
    max_shifts_per_nurse = min_shifts_per_nurse;
  } else {
    max_shifts_per_nurse = min_shifts_per_nurse + 1;
  }
  for (int n : all_nurses) {
    std::vector<BoolVar> shifts_worked;
    for (int d : all_days) {
      for (int s : all_shifts) {
        auto key = std::make_tuple(n, d, s);
        shifts_worked.push_back(shifts[key]);
      }
    }
    cp_model.AddLessOrEqual(min_shifts_per_nurse,
                            LinearExpr::Sum(shifts_worked));
    cp_model.AddLessOrEqual(LinearExpr::Sum(shifts_worked),
                            max_shifts_per_nurse);
  }

  Model model;
  SatParameters parameters;
  parameters.set_linearization_level(0);
  // Enumerate all solutions.
  parameters.set_enumerate_all_solutions(true);
  model.Add(NewSatParameters(parameters));

  // Display the first five solutions.
  // Create an atomic Boolean that will be periodically checked by the limit.
  std::atomic<bool> stopped(false);
  model.GetOrCreate<TimeLimit>()->RegisterExternalBooleanAsLimit(&stopped);

  const int kSolutionLimit = 5;
  int num_solutions = 0;
  model.Add(NewFeasibleSolutionObserver([&](const CpSolverResponse& r) {
    LOG(INFO) << "Solution " << num_solutions;
    for (int d : all_days) {
      LOG(INFO) << "Day " << std::to_string(d);
      for (int n : all_nurses) {
        bool is_working = false;
        for (int s : all_shifts) {
          auto key = std::make_tuple(n, d, s);
          if (SolutionIntegerValue(r, shifts[key])) {
            is_working = true;
            LOG(INFO) << "  Nurse " << std::to_string(n) << " works shift "
                      << std::to_string(s);
          }
        }
        if (!is_working) {
          LOG(INFO) << "  Nurse " << std::to_string(n) << " does not work";
        }
      }
    }
    num_solutions++;
    if (num_solutions >= kSolutionLimit) {
      stopped = true;
      LOG(INFO) << "Stop search after " << kSolutionLimit << " solutions.";
    }
  }));

  const CpSolverResponse response = SolveCpModel(cp_model.Build(), &model);

  // Statistics.
  LOG(INFO) << "Statistics";
  LOG(INFO) << CpSolverResponseStats(response);
  LOG(INFO) << "solutions found : " << std::to_string(num_solutions);
}

}  // namespace sat
}  // namespace operations_research

int main() {
  operations_research::sat::NurseSat();
  return EXIT_SUCCESS;
}

Java

package com.google.ortools.sat.samples;
import com.google.ortools.Loader;
import com.google.ortools.sat.CpModel;
import com.google.ortools.sat.CpSolver;
import com.google.ortools.sat.CpSolverSolutionCallback;
import com.google.ortools.sat.CpSolverStatus;
import com.google.ortools.sat.LinearExpr;
import com.google.ortools.sat.LinearExprBuilder;
import com.google.ortools.sat.Literal;
import java.util.ArrayList;
import java.util.List;
import java.util.stream.IntStream;

/** Nurses problem. */
public class NursesSat {
  public static void main(String[] args) {
    Loader.loadNativeLibraries();
    final int numNurses = 4;
    final int numDays = 3;
    final int numShifts = 3;

    final int[] allNurses = IntStream.range(0, numNurses).toArray();
    final int[] allDays = IntStream.range(0, numDays).toArray();
    final int[] allShifts = IntStream.range(0, numShifts).toArray();

    // Creates the model.
    CpModel model = new CpModel();

    // Creates shift variables.
    // shifts[(n, d, s)]: nurse 'n' works shift 's' on day 'd'.
    Literal[][][] shifts = new Literal[numNurses][numDays][numShifts];
    for (int n : allNurses) {
      for (int d : allDays) {
        for (int s : allShifts) {
          shifts[n][d][s] = model.newBoolVar("shifts_n" + n + "d" + d + "s" + s);
        }
      }
    }

    // Each shift is assigned to exactly one nurse in the schedule period.
    for (int d : allDays) {
      for (int s : allShifts) {
        List<Literal> nurses = new ArrayList<>();
        for (int n : allNurses) {
          nurses.add(shifts[n][d][s]);
        }
        model.addExactlyOne(nurses);
      }
    }

    // Each nurse works at most one shift per day.
    for (int n : allNurses) {
      for (int d : allDays) {
        List<Literal> work = new ArrayList<>();
        for (int s : allShifts) {
          work.add(shifts[n][d][s]);
        }
        model.addAtMostOne(work);
      }
    }

    // Try to distribute the shifts evenly, so that each nurse works
    // minShiftsPerNurse shifts. If this is not possible, because the total
    // number of shifts is not divisible by the number of nurses, some nurses will
    // be assigned one more shift.
    int minShiftsPerNurse = (numShifts * numDays) / numNurses;
    int maxShiftsPerNurse;
    if ((numShifts * numDays) % numNurses == 0) {
      maxShiftsPerNurse = minShiftsPerNurse;
    } else {
      maxShiftsPerNurse = minShiftsPerNurse + 1;
    }
    for (int n : allNurses) {
      LinearExprBuilder shiftsWorked = LinearExpr.newBuilder();
      for (int d : allDays) {
        for (int s : allShifts) {
          shiftsWorked.add(shifts[n][d][s]);
        }
      }
      model.addLinearConstraint(shiftsWorked, minShiftsPerNurse, maxShiftsPerNurse);
    }

    CpSolver solver = new CpSolver();
    solver.getParameters().setLinearizationLevel(0);
    // Tell the solver to enumerate all solutions.
    solver.getParameters().setEnumerateAllSolutions(true);

    // Display the first five solutions.
    final int solutionLimit = 5;
    class VarArraySolutionPrinterWithLimit extends CpSolverSolutionCallback {
      public VarArraySolutionPrinterWithLimit(
          int[] allNurses, int[] allDays, int[] allShifts, Literal[][][] shifts, int limit) {
        solutionCount = 0;
        this.allNurses = allNurses;
        this.allDays = allDays;
        this.allShifts = allShifts;
        this.shifts = shifts;
        solutionLimit = limit;
      }

      @Override
      public void onSolutionCallback() {
        System.out.printf("Solution #%d:%n", solutionCount);
        for (int d : allDays) {
          System.out.printf("Day %d%n", d);
          for (int n : allNurses) {
            boolean isWorking = false;
            for (int s : allShifts) {
              if (booleanValue(shifts[n][d][s])) {
                isWorking = true;
                System.out.printf("  Nurse %d work shift %d%n", n, s);
              }
            }
            if (!isWorking) {
              System.out.printf("  Nurse %d does not work%n", n);
            }
          }
        }
        solutionCount++;
        if (solutionCount >= solutionLimit) {
          System.out.printf("Stop search after %d solutions%n", solutionLimit);
          stopSearch();
        }
      }

      public int getSolutionCount() {
        return solutionCount;
      }

      private int solutionCount;
      private final int[] allNurses;
      private final int[] allDays;
      private final int[] allShifts;
      private final Literal[][][] shifts;
      private final int solutionLimit;
    }

    VarArraySolutionPrinterWithLimit cb =
        new VarArraySolutionPrinterWithLimit(allNurses, allDays, allShifts, shifts, solutionLimit);

    // Creates a solver and solves the model.
    CpSolverStatus status = solver.solve(model, cb);
    System.out.println("Status: " + status);
    System.out.println(cb.getSolutionCount() + " solutions found.");

    // Statistics.
    System.out.println("Statistics");
    System.out.printf("  conflicts: %d%n", solver.numConflicts());
    System.out.printf("  branches : %d%n", solver.numBranches());
    System.out.printf("  wall time: %f s%n", solver.wallTime());
  }

  private NursesSat() {}
}

C#‎

using System;
using System.Collections.Generic;
using System.IO;
using System.Linq;
using Google.OrTools.Sat;

public class NursesSat
{
    public class SolutionPrinter : CpSolverSolutionCallback
    {
        public SolutionPrinter(int[] allNurses, int[] allDays, int[] allShifts,
                               Dictionary<(int, int, int), BoolVar> shifts, int limit)
        {
            solutionCount_ = 0;
            allNurses_ = allNurses;
            allDays_ = allDays;
            allShifts_ = allShifts;
            shifts_ = shifts;
            solutionLimit_ = limit;
        }

        public override void OnSolutionCallback()
        {
            Console.WriteLine($"Solution #{solutionCount_}:");
            foreach (int d in allDays_)
            {
                Console.WriteLine($"Day {d}");
                foreach (int n in allNurses_)
                {
                    bool isWorking = false;
                    foreach (int s in allShifts_)
                    {
                        if (Value(shifts_[(n, d, s)]) == 1L)
                        {
                            isWorking = true;
                            Console.WriteLine($"  Nurse {n} work shift {s}");
                        }
                    }
                    if (!isWorking)
                    {
                        Console.WriteLine($"  Nurse {d} does not work");
                    }
                }
            }
            solutionCount_++;
            if (solutionCount_ >= solutionLimit_)
            {
                Console.WriteLine($"Stop search after {solutionLimit_} solutions");
                StopSearch();
            }
        }

        public int SolutionCount()
        {
            return solutionCount_;
        }

        private int solutionCount_;
        private int[] allNurses_;
        private int[] allDays_;
        private int[] allShifts_;
        private Dictionary<(int, int, int), BoolVar> shifts_;
        private int solutionLimit_;
    }

    public static void Main(String[] args)
    {
        const int numNurses = 4;
        const int numDays = 3;
        const int numShifts = 3;

        int[] allNurses = Enumerable.Range(0, numNurses).ToArray();
        int[] allDays = Enumerable.Range(0, numDays).ToArray();
        int[] allShifts = Enumerable.Range(0, numShifts).ToArray();

        // Creates the model.
        CpModel model = new CpModel();
        model.Model.Variables.Capacity = numNurses * numDays * numShifts;

        // Creates shift variables.
        // shifts[(n, d, s)]: nurse 'n' works shift 's' on day 'd'.
        Dictionary<(int, int, int), BoolVar> shifts =
            new Dictionary<(int, int, int), BoolVar>(numNurses * numDays * numShifts);
        foreach (int n in allNurses)
        {
            foreach (int d in allDays)
            {
                foreach (int s in allShifts)
                {
                    shifts.Add((n, d, s), model.NewBoolVar($"shifts_n{n}d{d}s{s}"));
                }
            }
        }

        // Each shift is assigned to exactly one nurse in the schedule period.
        List<ILiteral> literals = new List<ILiteral>();
        foreach (int d in allDays)
        {
            foreach (int s in allShifts)
            {
                foreach (int n in allNurses)
                {
                    literals.Add(shifts[(n, d, s)]);
                }
                model.AddExactlyOne(literals);
                literals.Clear();
            }
        }

        // Each nurse works at most one shift per day.
        foreach (int n in allNurses)
        {
            foreach (int d in allDays)
            {
                foreach (int s in allShifts)
                {
                    literals.Add(shifts[(n, d, s)]);
                }
                model.AddAtMostOne(literals);
                literals.Clear();
            }
        }

        // Try to distribute the shifts evenly, so that each nurse works
        // minShiftsPerNurse shifts. If this is not possible, because the total
        // number of shifts is not divisible by the number of nurses, some nurses will
        // be assigned one more shift.
        int minShiftsPerNurse = (numShifts * numDays) / numNurses;
        int maxShiftsPerNurse;
        if ((numShifts * numDays) % numNurses == 0)
        {
            maxShiftsPerNurse = minShiftsPerNurse;
        }
        else
        {
            maxShiftsPerNurse = minShiftsPerNurse + 1;
        }

        List<IntVar> shiftsWorked = new List<IntVar>();
        foreach (int n in allNurses)
        {
            foreach (int d in allDays)
            {
                foreach (int s in allShifts)
                {
                    shiftsWorked.Add(shifts[(n, d, s)]);
                }
            }
            model.AddLinearConstraint(LinearExpr.Sum(shiftsWorked), minShiftsPerNurse, maxShiftsPerNurse);
            shiftsWorked.Clear();
        }

        CpSolver solver = new CpSolver();
        // Tell the solver to enumerate all solutions.
        solver.StringParameters += "linearization_level:0 " + "enumerate_all_solutions:true ";

        // Display the first five solutions.
        const int solutionLimit = 5;
        SolutionPrinter cb = new SolutionPrinter(allNurses, allDays, allShifts, shifts, solutionLimit);

        // Solve
        CpSolverStatus status = solver.Solve(model, cb);
        Console.WriteLine($"Solve status: {status}");

        Console.WriteLine("Statistics");
        Console.WriteLine($"  conflicts: {solver.NumConflicts()}");
        Console.WriteLine($"  branches : {solver.NumBranches()}");
        Console.WriteLine($"  wall time: {solver.WallTime()}s");
    }
}

קביעת פגישות באמצעות בקשות להחלפה

בקטע הזה, ניקח את הדוגמה הקודמת ונוסיף בקשות לאחות עבור לשינויים ספציפיים. לאחר מכן אנחנו מחפשים לוח זמנים שמגדיל את מספר הבקשות שמולאו. ברוב הבעיות שקשורות לתזמון, עדיף לבצע אופטימיזציה של פונקציית יעד, בדרך כלל לא פרקטי להדפיס את כל לוחות הזמנים האפשריים.

בדוגמה הזו יש אותם מגבלות כמו בדוגמה הקודמת.

ייבוא הספריות

הקוד הבא מייבא את הספרייה הנדרשת.

Python

from typing import Union

from ortools.sat.python import cp_model

C++‎

#include <stdlib.h>

#include <cstdint>
#include <map>
#include <numeric>
#include <string>
#include <tuple>
#include <vector>

#include "absl/strings/str_format.h"
#include "ortools/base/logging.h"
#include "ortools/sat/cp_model.h"
#include "ortools/sat/cp_model.pb.h"
#include "ortools/sat/cp_model_solver.h"

Java

import com.google.ortools.Loader;
import com.google.ortools.sat.CpModel;
import com.google.ortools.sat.CpSolver;
import com.google.ortools.sat.CpSolverStatus;
import com.google.ortools.sat.LinearExpr;
import com.google.ortools.sat.LinearExprBuilder;
import com.google.ortools.sat.Literal;
import java.util.ArrayList;
import java.util.List;
import java.util.stream.IntStream;

C#‎

using System;
using System.Collections.Generic;
using System.Linq;
using Google.OrTools.Sat;

נתונים עבור הדוגמה

הנתונים לדוגמה הזו מוצגים אחרי זה.

Python

num_nurses = 5
num_shifts = 3
num_days = 7
all_nurses = range(num_nurses)
all_shifts = range(num_shifts)
all_days = range(num_days)
shift_requests = [
    [[0, 0, 1], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 1], [0, 1, 0], [0, 0, 1]],
    [[0, 0, 0], [0, 0, 0], [0, 1, 0], [0, 1, 0], [1, 0, 0], [0, 0, 0], [0, 0, 1]],
    [[0, 1, 0], [0, 1, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 1, 0], [0, 0, 0]],
    [[0, 0, 1], [0, 0, 0], [1, 0, 0], [0, 1, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0]],
    [[0, 0, 0], [0, 0, 1], [0, 1, 0], [0, 0, 0], [1, 0, 0], [0, 1, 0], [0, 0, 0]],
]

C++‎

const int num_nurses = 5;
const int num_days = 7;
const int num_shifts = 3;

std::vector<int> all_nurses(num_nurses);
std::iota(all_nurses.begin(), all_nurses.end(), 0);

std::vector<int> all_days(num_days);
std::iota(all_days.begin(), all_days.end(), 0);

std::vector<int> all_shifts(num_shifts);
std::iota(all_shifts.begin(), all_shifts.end(), 0);

std::vector<std::vector<std::vector<int64_t>>> shift_requests = {
    {
        {0, 0, 1},
        {0, 0, 0},
        {0, 0, 0},
        {0, 0, 0},
        {0, 0, 1},
        {0, 1, 0},
        {0, 0, 1},
    },
    {
        {0, 0, 0},
        {0, 0, 0},
        {0, 1, 0},
        {0, 1, 0},
        {1, 0, 0},
        {0, 0, 0},
        {0, 0, 1},
    },
    {
        {0, 1, 0},
        {0, 1, 0},
        {0, 0, 0},
        {1, 0, 0},
        {0, 0, 0},
        {0, 1, 0},
        {0, 0, 0},
    },
    {
        {0, 0, 1},
        {0, 0, 0},
        {1, 0, 0},
        {0, 1, 0},
        {0, 0, 0},
        {1, 0, 0},
        {0, 0, 0},
    },
    {
        {0, 0, 0},
        {0, 0, 1},
        {0, 1, 0},
        {0, 0, 0},
        {1, 0, 0},
        {0, 1, 0},
        {0, 0, 0},
    },
};

Java

final int numNurses = 5;
final int numDays = 7;
final int numShifts = 3;

final int[] allNurses = IntStream.range(0, numNurses).toArray();
final int[] allDays = IntStream.range(0, numDays).toArray();
final int[] allShifts = IntStream.range(0, numShifts).toArray();

final int[][][] shiftRequests = new int[][][] {
    {
        {0, 0, 1},
        {0, 0, 0},
        {0, 0, 0},
        {0, 0, 0},
        {0, 0, 1},
        {0, 1, 0},
        {0, 0, 1},
    },
    {
        {0, 0, 0},
        {0, 0, 0},
        {0, 1, 0},
        {0, 1, 0},
        {1, 0, 0},
        {0, 0, 0},
        {0, 0, 1},
    },
    {
        {0, 1, 0},
        {0, 1, 0},
        {0, 0, 0},
        {1, 0, 0},
        {0, 0, 0},
        {0, 1, 0},
        {0, 0, 0},
    },
    {
        {0, 0, 1},
        {0, 0, 0},
        {1, 0, 0},
        {0, 1, 0},
        {0, 0, 0},
        {1, 0, 0},
        {0, 0, 0},
    },
    {
        {0, 0, 0},
        {0, 0, 1},
        {0, 1, 0},
        {0, 0, 0},
        {1, 0, 0},
        {0, 1, 0},
        {0, 0, 0},
    },
};

C#‎

const int numNurses = 5;
const int numDays = 7;
const int numShifts = 3;

int[] allNurses = Enumerable.Range(0, numNurses).ToArray();
int[] allDays = Enumerable.Range(0, numDays).ToArray();
int[] allShifts = Enumerable.Range(0, numShifts).ToArray();

int[,,] shiftRequests = new int[,,] {
    {
        { 0, 0, 1 },
        { 0, 0, 0 },
        { 0, 0, 0 },
        { 0, 0, 0 },
        { 0, 0, 1 },
        { 0, 1, 0 },
        { 0, 0, 1 },
    },
    {
        { 0, 0, 0 },
        { 0, 0, 0 },
        { 0, 1, 0 },
        { 0, 1, 0 },
        { 1, 0, 0 },
        { 0, 0, 0 },
        { 0, 0, 1 },
    },
    {
        { 0, 1, 0 },
        { 0, 1, 0 },
        { 0, 0, 0 },
        { 1, 0, 0 },
        { 0, 0, 0 },
        { 0, 1, 0 },
        { 0, 0, 0 },
    },
    {
        { 0, 0, 1 },
        { 0, 0, 0 },
        { 1, 0, 0 },
        { 0, 1, 0 },
        { 0, 0, 0 },
        { 1, 0, 0 },
        { 0, 0, 0 },
    },
    {
        { 0, 0, 0 },
        { 0, 0, 1 },
        { 0, 1, 0 },
        { 0, 0, 0 },
        { 1, 0, 0 },
        { 0, 1, 0 },
        { 0, 0, 0 },
    },
};

יצירת המודל

הקוד הבא יוצר את המודל.

Python

model = cp_model.CpModel()

C++‎

CpModelBuilder cp_model;

Java

CpModel model = new CpModel();

C#‎

CpModel model = new CpModel();

יצירת המשתנים

הקוד הבא הוא מערך של משתנים בשביל הבעיה.

בנוסף למשתנים מהדוגמה הקודמת, הנתונים מכילים גם קבוצת שלשות, שתואמת לשלוש המחליפות ביום. כל רכיב ערך המשולש הוא 0 או 1, שמציין אם נשלחה בקשה לשינוי. לדוגמה, שלוש פעמים [0, 0, 1] במיקום החמישי בשורה 1 מציינת שאחות 1 בקשות Shift 3 ביום 5.

Python

shifts = {}
for n in all_nurses:
    for d in all_days:
        for s in all_shifts:
            shifts[(n, d, s)] = model.new_bool_var(f"shift_n{n}_d{d}_s{s}")

C++‎

std::map<std::tuple<int, int, int>, BoolVar> shifts;
for (int n : all_nurses) {
  for (int d : all_days) {
    for (int s : all_shifts) {
      auto key = std::make_tuple(n, d, s);
      shifts[key] = cp_model.NewBoolVar().WithName(
          absl::StrFormat("shift_n%dd%ds%d", n, d, s));
    }
  }
}

Java

Literal[][][] shifts = new Literal[numNurses][numDays][numShifts];
for (int n : allNurses) {
  for (int d : allDays) {
    for (int s : allShifts) {
      shifts[n][d][s] = model.newBoolVar("shifts_n" + n + "d" + d + "s" + s);
    }
  }
}

C#‎

Dictionary<Tuple<int, int, int>, IntVar> shifts = new Dictionary<Tuple<int, int, int>, IntVar>();
foreach (int n in allNurses)
{
    foreach (int d in allDays)
    {
        foreach (int s in allShifts)
        {
            shifts.Add(Tuple.Create(n, d, s), model.NewBoolVar($"shifts_n{n}d{d}s{s}"));
        }
    }
}

יצירת האילוצים

הקוד הבא יוצר את המגבלות לבעיה.

Python

for d in all_days:
    for s in all_shifts:
        model.add_exactly_one(shifts[(n, d, s)] for n in all_nurses)

C++‎

for (int d : all_days) {
  for (int s : all_shifts) {
    std::vector<BoolVar> nurses;
    for (int n : all_nurses) {
      auto key = std::make_tuple(n, d, s);
      nurses.push_back(shifts[key]);
    }
    cp_model.AddExactlyOne(nurses);
  }
}

Java

for (int d : allDays) {
  for (int s : allShifts) {
    List<Literal> nurses = new ArrayList<>();
    for (int n : allNurses) {
      nurses.add(shifts[n][d][s]);
    }
    model.addExactlyOne(nurses);
  }
}

C#‎

foreach (int d in allDays)
{
    foreach (int s in allShifts)
    {
        IntVar[] x = new IntVar[numNurses];
        foreach (int n in allNurses)
        {
            var key = Tuple.Create(n, d, s);
            x[n] = shifts[key];
        }
        model.Add(LinearExpr.Sum(x) == 1);
    }
}

Python

for n in all_nurses:
    for d in all_days:
        model.add_at_most_one(shifts[(n, d, s)] for s in all_shifts)

C++‎

for (int n : all_nurses) {
  for (int d : all_days) {
    std::vector<BoolVar> work;
    for (int s : all_shifts) {
      auto key = std::make_tuple(n, d, s);
      work.push_back(shifts[key]);
    }
    cp_model.AddAtMostOne(work);
  }
}

Java

for (int n : allNurses) {
  for (int d : allDays) {
    List<Literal> work = new ArrayList<>();
    for (int s : allShifts) {
      work.add(shifts[n][d][s]);
    }
    model.addAtMostOne(work);
  }
}

C#‎

foreach (int n in allNurses)
{
    foreach (int d in allDays)
    {
        IntVar[] x = new IntVar[numShifts];
        foreach (int s in allShifts)
        {
            var key = Tuple.Create(n, d, s);
            x[s] = shifts[key];
        }
        model.Add(LinearExpr.Sum(x) <= 1);
    }
}

Python

# Try to distribute the shifts evenly, so that each nurse works
# min_shifts_per_nurse shifts. If this is not possible, because the total
# number of shifts is not divisible by the number of nurses, some nurses will
# be assigned one more shift.
min_shifts_per_nurse = (num_shifts * num_days) // num_nurses
if num_shifts * num_days % num_nurses == 0:
    max_shifts_per_nurse = min_shifts_per_nurse
else:
    max_shifts_per_nurse = min_shifts_per_nurse + 1
for n in all_nurses:
    num_shifts_worked: Union[cp_model.LinearExpr, int] = 0
    for d in all_days:
        for s in all_shifts:
            num_shifts_worked += shifts[(n, d, s)]
    model.add(min_shifts_per_nurse <= num_shifts_worked)
    model.add(num_shifts_worked <= max_shifts_per_nurse)

C++‎

// Try to distribute the shifts evenly, so that each nurse works
// min_shifts_per_nurse shifts. If this is not possible, because the total
// number of shifts is not divisible by the number of nurses, some nurses will
// be assigned one more shift.
int min_shifts_per_nurse = (num_shifts * num_days) / num_nurses;
int max_shifts_per_nurse;
if ((num_shifts * num_days) % num_nurses == 0) {
  max_shifts_per_nurse = min_shifts_per_nurse;
} else {
  max_shifts_per_nurse = min_shifts_per_nurse + 1;
}
for (int n : all_nurses) {
  LinearExpr num_worked_shifts;
  for (int d : all_days) {
    for (int s : all_shifts) {
      auto key = std::make_tuple(n, d, s);
      num_worked_shifts += shifts[key];
    }
  }
  cp_model.AddLessOrEqual(min_shifts_per_nurse, num_worked_shifts);
  cp_model.AddLessOrEqual(num_worked_shifts, max_shifts_per_nurse);
}

Java

// Try to distribute the shifts evenly, so that each nurse works
// minShiftsPerNurse shifts. If this is not possible, because the total
// number of shifts is not divisible by the number of nurses, some nurses will
// be assigned one more shift.
int minShiftsPerNurse = (numShifts * numDays) / numNurses;
int maxShiftsPerNurse;
if ((numShifts * numDays) % numNurses == 0) {
  maxShiftsPerNurse = minShiftsPerNurse;
} else {
  maxShiftsPerNurse = minShiftsPerNurse + 1;
}
for (int n : allNurses) {
  LinearExprBuilder numShiftsWorked = LinearExpr.newBuilder();
  for (int d : allDays) {
    for (int s : allShifts) {
      numShiftsWorked.add(shifts[n][d][s]);
    }
  }
  model.addLinearConstraint(numShiftsWorked, minShiftsPerNurse, maxShiftsPerNurse);
}

C#‎

// Try to distribute the shifts evenly, so that each nurse works
// minShiftsPerNurse shifts. If this is not possible, because the total
// number of shifts is not divisible by the number of nurses, some nurses will
// be assigned one more shift.
int minShiftsPerNurse = (numShifts * numDays) / numNurses;
int maxShiftsPerNurse;
if ((numShifts * numDays) % numNurses == 0)
{
    maxShiftsPerNurse = minShiftsPerNurse;
}
else
{
    maxShiftsPerNurse = minShiftsPerNurse + 1;
}
foreach (int n in allNurses)
{
    IntVar[] numShiftsWorked = new IntVar[numDays * numShifts];
    foreach (int d in allDays)
    {
        foreach (int s in allShifts)
        {
            var key = Tuple.Create(n, d, s);
            numShiftsWorked[d * numShifts + s] = shifts[key];
        }
    }
    model.AddLinearConstraint(LinearExpr.Sum(numShiftsWorked), minShiftsPerNurse, maxShiftsPerNurse);
}

מטרת הדוגמה

אנחנו רוצים לבצע אופטימיזציה של פונקציית היעד הבאה.

Python

model.maximize(
    sum(
        shift_requests[n][d][s] * shifts[(n, d, s)]
        for n in all_nurses
        for d in all_days
        for s in all_shifts
    )
)

C++‎

LinearExpr objective_expr;
for (int n : all_nurses) {
  for (int d : all_days) {
    for (int s : all_shifts) {
      if (shift_requests[n][d][s] == 1) {
        auto key = std::make_tuple(n, d, s);
        objective_expr += shifts[key] * shift_requests[n][d][s];
      }
    }
  }
}
cp_model.Maximize(objective_expr);

Java

LinearExprBuilder obj = LinearExpr.newBuilder();
for (int n : allNurses) {
  for (int d : allDays) {
    for (int s : allShifts) {
      obj.addTerm(shifts[n][d][s], shiftRequests[n][d][s]);
    }
  }
}
model.maximize(obj);

C#‎

IntVar[] flatShifts = new IntVar[numNurses * numDays * numShifts];
int[] flatShiftRequests = new int[numNurses * numDays * numShifts];
foreach (int n in allNurses)
{
    foreach (int d in allDays)
    {
        foreach (int s in allShifts)
        {
            var key = Tuple.Create(n, d, s);
            flatShifts[n * numDays * numShifts + d * numShifts + s] = shifts[key];
            flatShiftRequests[n * numDays * numShifts + d * numShifts + s] = shiftRequests[n, d, s];
        }
    }
}
model.Maximize(LinearExpr.WeightedSum(flatShifts, flatShiftRequests));

מכיוון שהערך של shift_requests[n][d][s] * shifts[(n, d, s) הוא 1 אם הוקצתה משתנה s לאחות n ביום d וגם שהאחות ביקשה התאמה (ואחרת 0), המטרה היא השינוי במספר המטלות שעומדות בבקשה.

הפעלת הפותר

הקוד הבא מפעיל את הפותר.

Python

solver = cp_model.CpSolver()
status = solver.solve(model)

C++‎

const CpSolverResponse response = Solve(cp_model.Build());

Java

CpSolver solver = new CpSolver();
CpSolverStatus status = solver.solve(model);

C#‎

CpSolver solver = new CpSolver();
CpSolverStatus status = solver.Solve(model);
Console.WriteLine($"Solve status: {status}");

הצגת התוצאות

הקוד הבא מציג את הפלט הבא, שכולל אפשרות לוח זמנים (אם כי ייתכן שזה לא היחיד). הפלט מראה איזה שינוי בקשות של מטלות שהוגשו ואת מספר הבקשות שהוגשו.

Python

if status == cp_model.OPTIMAL:
    print("Solution:")
    for d in all_days:
        print("Day", d)
        for n in all_nurses:
            for s in all_shifts:
                if solver.value(shifts[(n, d, s)]) == 1:
                    if shift_requests[n][d][s] == 1:
                        print("Nurse", n, "works shift", s, "(requested).")
                    else:
                        print("Nurse", n, "works shift", s, "(not requested).")
        print()
    print(
        f"Number of shift requests met = {solver.objective_value}",
        f"(out of {num_nurses * min_shifts_per_nurse})",
    )
else:
    print("No optimal solution found !")

C++‎

if (response.status() == CpSolverStatus::OPTIMAL) {
  LOG(INFO) << "Solution:";
  for (int d : all_days) {
    LOG(INFO) << "Day " << std::to_string(d);
    for (int n : all_nurses) {
      for (int s : all_shifts) {
        auto key = std::make_tuple(n, d, s);
        if (SolutionIntegerValue(response, shifts[key]) == 1) {
          if (shift_requests[n][d][s] == 1) {
            LOG(INFO) << "  Nurse " << std::to_string(n) << " works shift "
                      << std::to_string(s) << " (requested).";
          } else {
            LOG(INFO) << "  Nurse " << std::to_string(n) << " works shift "
                      << std::to_string(s) << " (not requested).";
          }
        }
      }
    }
    LOG(INFO) << "";
  }
  LOG(INFO) << "Number of shift requests met = " << response.objective_value()
            << " (out of " << num_nurses * min_shifts_per_nurse << ")";
} else {
  LOG(INFO) << "No optimal solution found !";
}

Java

if (status == CpSolverStatus.OPTIMAL || status == CpSolverStatus.FEASIBLE) {
  System.out.printf("Solution:%n");
  for (int d : allDays) {
    System.out.printf("Day %d%n", d);
    for (int n : allNurses) {
      for (int s : allShifts) {
        if (solver.booleanValue(shifts[n][d][s])) {
          if (shiftRequests[n][d][s] == 1) {
            System.out.printf("  Nurse %d works shift %d (requested).%n", n, s);
          } else {
            System.out.printf("  Nurse %d works shift %d (not requested).%n", n, s);
          }
        }
      }
    }
  }
  System.out.printf("Number of shift requests met = %f (out of %d)%n", solver.objectiveValue(),
      numNurses * minShiftsPerNurse);
} else {
  System.out.printf("No optimal solution found !");
}

C#‎

if (status == CpSolverStatus.Optimal || status == CpSolverStatus.Feasible)
{
    Console.WriteLine("Solution:");
    foreach (int d in allDays)
    {
        Console.WriteLine($"Day {d}");
        foreach (int n in allNurses)
        {
            bool isWorking = false;
            foreach (int s in allShifts)
            {
                var key = Tuple.Create(n, d, s);
                if (solver.Value(shifts[key]) == 1L)
                {
                    if (shiftRequests[n, d, s] == 1)
                    {
                        Console.WriteLine($"  Nurse {n} work shift {s} (requested).");
                    }
                    else
                    {
                        Console.WriteLine($"  Nurse {n} work shift {s} (not requested).");
                    }
                }
            }
        }
    }
    Console.WriteLine(
        $"Number of shift requests met = {solver.ObjectiveValue} (out of {numNurses * minShiftsPerNurse}).");
}
else
{
    Console.WriteLine("No solution found.");
}

כשמריצים את התוכנית, הפלט הבא מוצג:

Day 0
Nurse 1 works shift 0 (not requested).
Nurse 2 works shift 1 (requested).
Nurse 3 works shift 2 (requested).

Day 1
Nurse 0 works shift 0 (not requested).
Nurse 2 works shift 1 (requested).
Nurse 4 works shift 2 (requested).

Day 2
Nurse 1 works shift 2 (not requested).
Nurse 3 works shift 0 (requested).
Nurse 4 works shift 1 (requested).

Day 3
Nurse 2 works shift 0 (requested).
Nurse 3 works shift 1 (requested).
Nurse 4 works shift 2 (not requested).

Day 4
Nurse 0 works shift 2 (requested).
Nurse 1 works shift 0 (requested).
Nurse 4 works shift 1 (not requested).

Day 5
Nurse 0 works shift 2 (not requested).
Nurse 2 works shift 1 (requested).
Nurse 3 works shift 0 (requested).

Day 6
Nurse 0 works shift 1 (not requested).
Nurse 1 works shift 2 (requested).
Nurse 4 works shift 0 (not requested).

Statistics
  - Number of shift requests met = 13 (out of 20 )
  - wall time       : 0.003571 s

כל התוכנית

כאן מוצגת התוכנית המלאה לתזמון באמצעות בקשות לשינוי.

Python

"""Nurse scheduling problem with shift requests."""
from typing import Union

from ortools.sat.python import cp_model


def main() -> None:
    # This program tries to find an optimal assignment of nurses to shifts
    # (3 shifts per day, for 7 days), subject to some constraints (see below).
    # Each nurse can request to be assigned to specific shifts.
    # The optimal assignment maximizes the number of fulfilled shift requests.
    num_nurses = 5
    num_shifts = 3
    num_days = 7
    all_nurses = range(num_nurses)
    all_shifts = range(num_shifts)
    all_days = range(num_days)
    shift_requests = [
        [[0, 0, 1], [0, 0, 0], [0, 0, 0], [0, 0, 0], [0, 0, 1], [0, 1, 0], [0, 0, 1]],
        [[0, 0, 0], [0, 0, 0], [0, 1, 0], [0, 1, 0], [1, 0, 0], [0, 0, 0], [0, 0, 1]],
        [[0, 1, 0], [0, 1, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0], [0, 1, 0], [0, 0, 0]],
        [[0, 0, 1], [0, 0, 0], [1, 0, 0], [0, 1, 0], [0, 0, 0], [1, 0, 0], [0, 0, 0]],
        [[0, 0, 0], [0, 0, 1], [0, 1, 0], [0, 0, 0], [1, 0, 0], [0, 1, 0], [0, 0, 0]],
    ]

    # Creates the model.
    model = cp_model.CpModel()

    # Creates shift variables.
    # shifts[(n, d, s)]: nurse 'n' works shift 's' on day 'd'.
    shifts = {}
    for n in all_nurses:
        for d in all_days:
            for s in all_shifts:
                shifts[(n, d, s)] = model.new_bool_var(f"shift_n{n}_d{d}_s{s}")

    # Each shift is assigned to exactly one nurse in .
    for d in all_days:
        for s in all_shifts:
            model.add_exactly_one(shifts[(n, d, s)] for n in all_nurses)

    # Each nurse works at most one shift per day.
    for n in all_nurses:
        for d in all_days:
            model.add_at_most_one(shifts[(n, d, s)] for s in all_shifts)

    # Try to distribute the shifts evenly, so that each nurse works
    # min_shifts_per_nurse shifts. If this is not possible, because the total
    # number of shifts is not divisible by the number of nurses, some nurses will
    # be assigned one more shift.
    min_shifts_per_nurse = (num_shifts * num_days) // num_nurses
    if num_shifts * num_days % num_nurses == 0:
        max_shifts_per_nurse = min_shifts_per_nurse
    else:
        max_shifts_per_nurse = min_shifts_per_nurse + 1
    for n in all_nurses:
        num_shifts_worked: Union[cp_model.LinearExpr, int] = 0
        for d in all_days:
            for s in all_shifts:
                num_shifts_worked += shifts[(n, d, s)]
        model.add(min_shifts_per_nurse <= num_shifts_worked)
        model.add(num_shifts_worked <= max_shifts_per_nurse)

    model.maximize(
        sum(
            shift_requests[n][d][s] * shifts[(n, d, s)]
            for n in all_nurses
            for d in all_days
            for s in all_shifts
        )
    )

    # Creates the solver and solve.
    solver = cp_model.CpSolver()
    status = solver.solve(model)

    if status == cp_model.OPTIMAL:
        print("Solution:")
        for d in all_days:
            print("Day", d)
            for n in all_nurses:
                for s in all_shifts:
                    if solver.value(shifts[(n, d, s)]) == 1:
                        if shift_requests[n][d][s] == 1:
                            print("Nurse", n, "works shift", s, "(requested).")
                        else:
                            print("Nurse", n, "works shift", s, "(not requested).")
            print()
        print(
            f"Number of shift requests met = {solver.objective_value}",
            f"(out of {num_nurses * min_shifts_per_nurse})",
        )
    else:
        print("No optimal solution found !")

    # Statistics.
    print("\nStatistics")
    print(f"  - conflicts: {solver.num_conflicts}")
    print(f"  - branches : {solver.num_branches}")
    print(f"  - wall time: {solver.wall_time}s")


if __name__ == "__main__":
    main()

C++‎

// Nurse scheduling problem with shift requests.
#include <stdlib.h>

#include <cstdint>
#include <map>
#include <numeric>
#include <string>
#include <tuple>
#include <vector>

#include "absl/strings/str_format.h"
#include "ortools/base/logging.h"
#include "ortools/sat/cp_model.h"
#include "ortools/sat/cp_model.pb.h"
#include "ortools/sat/cp_model_solver.h"

namespace operations_research {
namespace sat {

void ScheduleRequestsSat() {
  const int num_nurses = 5;
  const int num_days = 7;
  const int num_shifts = 3;

  std::vector<int> all_nurses(num_nurses);
  std::iota(all_nurses.begin(), all_nurses.end(), 0);

  std::vector<int> all_days(num_days);
  std::iota(all_days.begin(), all_days.end(), 0);

  std::vector<int> all_shifts(num_shifts);
  std::iota(all_shifts.begin(), all_shifts.end(), 0);

  std::vector<std::vector<std::vector<int64_t>>> shift_requests = {
      {
          {0, 0, 1},
          {0, 0, 0},
          {0, 0, 0},
          {0, 0, 0},
          {0, 0, 1},
          {0, 1, 0},
          {0, 0, 1},
      },
      {
          {0, 0, 0},
          {0, 0, 0},
          {0, 1, 0},
          {0, 1, 0},
          {1, 0, 0},
          {0, 0, 0},
          {0, 0, 1},
      },
      {
          {0, 1, 0},
          {0, 1, 0},
          {0, 0, 0},
          {1, 0, 0},
          {0, 0, 0},
          {0, 1, 0},
          {0, 0, 0},
      },
      {
          {0, 0, 1},
          {0, 0, 0},
          {1, 0, 0},
          {0, 1, 0},
          {0, 0, 0},
          {1, 0, 0},
          {0, 0, 0},
      },
      {
          {0, 0, 0},
          {0, 0, 1},
          {0, 1, 0},
          {0, 0, 0},
          {1, 0, 0},
          {0, 1, 0},
          {0, 0, 0},
      },
  };

  // Creates the model.
  CpModelBuilder cp_model;

  // Creates shift variables.
  // shifts[(n, d, s)]: nurse 'n' works shift 's' on day 'd'.
  std::map<std::tuple<int, int, int>, BoolVar> shifts;
  for (int n : all_nurses) {
    for (int d : all_days) {
      for (int s : all_shifts) {
        auto key = std::make_tuple(n, d, s);
        shifts[key] = cp_model.NewBoolVar().WithName(
            absl::StrFormat("shift_n%dd%ds%d", n, d, s));
      }
    }
  }

  // Each shift is assigned to exactly one nurse in the schedule period.
  for (int d : all_days) {
    for (int s : all_shifts) {
      std::vector<BoolVar> nurses;
      for (int n : all_nurses) {
        auto key = std::make_tuple(n, d, s);
        nurses.push_back(shifts[key]);
      }
      cp_model.AddExactlyOne(nurses);
    }
  }

  // Each nurse works at most one shift per day.
  for (int n : all_nurses) {
    for (int d : all_days) {
      std::vector<BoolVar> work;
      for (int s : all_shifts) {
        auto key = std::make_tuple(n, d, s);
        work.push_back(shifts[key]);
      }
      cp_model.AddAtMostOne(work);
    }
  }

  // Try to distribute the shifts evenly, so that each nurse works
  // min_shifts_per_nurse shifts. If this is not possible, because the total
  // number of shifts is not divisible by the number of nurses, some nurses will
  // be assigned one more shift.
  int min_shifts_per_nurse = (num_shifts * num_days) / num_nurses;
  int max_shifts_per_nurse;
  if ((num_shifts * num_days) % num_nurses == 0) {
    max_shifts_per_nurse = min_shifts_per_nurse;
  } else {
    max_shifts_per_nurse = min_shifts_per_nurse + 1;
  }
  for (int n : all_nurses) {
    LinearExpr num_worked_shifts;
    for (int d : all_days) {
      for (int s : all_shifts) {
        auto key = std::make_tuple(n, d, s);
        num_worked_shifts += shifts[key];
      }
    }
    cp_model.AddLessOrEqual(min_shifts_per_nurse, num_worked_shifts);
    cp_model.AddLessOrEqual(num_worked_shifts, max_shifts_per_nurse);
  }

  LinearExpr objective_expr;
  for (int n : all_nurses) {
    for (int d : all_days) {
      for (int s : all_shifts) {
        if (shift_requests[n][d][s] == 1) {
          auto key = std::make_tuple(n, d, s);
          objective_expr += shifts[key] * shift_requests[n][d][s];
        }
      }
    }
  }
  cp_model.Maximize(objective_expr);

  const CpSolverResponse response = Solve(cp_model.Build());

  if (response.status() == CpSolverStatus::OPTIMAL) {
    LOG(INFO) << "Solution:";
    for (int d : all_days) {
      LOG(INFO) << "Day " << std::to_string(d);
      for (int n : all_nurses) {
        for (int s : all_shifts) {
          auto key = std::make_tuple(n, d, s);
          if (SolutionIntegerValue(response, shifts[key]) == 1) {
            if (shift_requests[n][d][s] == 1) {
              LOG(INFO) << "  Nurse " << std::to_string(n) << " works shift "
                        << std::to_string(s) << " (requested).";
            } else {
              LOG(INFO) << "  Nurse " << std::to_string(n) << " works shift "
                        << std::to_string(s) << " (not requested).";
            }
          }
        }
      }
      LOG(INFO) << "";
    }
    LOG(INFO) << "Number of shift requests met = " << response.objective_value()
              << " (out of " << num_nurses * min_shifts_per_nurse << ")";
  } else {
    LOG(INFO) << "No optimal solution found !";
  }

  // Statistics.
  LOG(INFO) << "Statistics";
  LOG(INFO) << CpSolverResponseStats(response);
}

}  // namespace sat
}  // namespace operations_research

int main() {
  operations_research::sat::ScheduleRequestsSat();
  return EXIT_SUCCESS;
}

Java

package com.google.ortools.sat.samples;
import com.google.ortools.Loader;
import com.google.ortools.sat.CpModel;
import com.google.ortools.sat.CpSolver;
import com.google.ortools.sat.CpSolverStatus;
import com.google.ortools.sat.LinearExpr;
import com.google.ortools.sat.LinearExprBuilder;
import com.google.ortools.sat.Literal;
import java.util.ArrayList;
import java.util.List;
import java.util.stream.IntStream;

/** Nurses problem with schedule requests. */
public class ScheduleRequestsSat {
  public static void main(String[] args) {
    Loader.loadNativeLibraries();
    final int numNurses = 5;
    final int numDays = 7;
    final int numShifts = 3;

    final int[] allNurses = IntStream.range(0, numNurses).toArray();
    final int[] allDays = IntStream.range(0, numDays).toArray();
    final int[] allShifts = IntStream.range(0, numShifts).toArray();

    final int[][][] shiftRequests = new int[][][] {
        {
            {0, 0, 1},
            {0, 0, 0},
            {0, 0, 0},
            {0, 0, 0},
            {0, 0, 1},
            {0, 1, 0},
            {0, 0, 1},
        },
        {
            {0, 0, 0},
            {0, 0, 0},
            {0, 1, 0},
            {0, 1, 0},
            {1, 0, 0},
            {0, 0, 0},
            {0, 0, 1},
        },
        {
            {0, 1, 0},
            {0, 1, 0},
            {0, 0, 0},
            {1, 0, 0},
            {0, 0, 0},
            {0, 1, 0},
            {0, 0, 0},
        },
        {
            {0, 0, 1},
            {0, 0, 0},
            {1, 0, 0},
            {0, 1, 0},
            {0, 0, 0},
            {1, 0, 0},
            {0, 0, 0},
        },
        {
            {0, 0, 0},
            {0, 0, 1},
            {0, 1, 0},
            {0, 0, 0},
            {1, 0, 0},
            {0, 1, 0},
            {0, 0, 0},
        },
    };

    // Creates the model.
    CpModel model = new CpModel();

    // Creates shift variables.
    // shifts[(n, d, s)]: nurse 'n' works shift 's' on day 'd'.
    Literal[][][] shifts = new Literal[numNurses][numDays][numShifts];
    for (int n : allNurses) {
      for (int d : allDays) {
        for (int s : allShifts) {
          shifts[n][d][s] = model.newBoolVar("shifts_n" + n + "d" + d + "s" + s);
        }
      }
    }

    // Each shift is assigned to exactly one nurse in the schedule period.
    for (int d : allDays) {
      for (int s : allShifts) {
        List<Literal> nurses = new ArrayList<>();
        for (int n : allNurses) {
          nurses.add(shifts[n][d][s]);
        }
        model.addExactlyOne(nurses);
      }
    }

    // Each nurse works at most one shift per day.
    for (int n : allNurses) {
      for (int d : allDays) {
        List<Literal> work = new ArrayList<>();
        for (int s : allShifts) {
          work.add(shifts[n][d][s]);
        }
        model.addAtMostOne(work);
      }
    }

    // Try to distribute the shifts evenly, so that each nurse works
    // minShiftsPerNurse shifts. If this is not possible, because the total
    // number of shifts is not divisible by the number of nurses, some nurses will
    // be assigned one more shift.
    int minShiftsPerNurse = (numShifts * numDays) / numNurses;
    int maxShiftsPerNurse;
    if ((numShifts * numDays) % numNurses == 0) {
      maxShiftsPerNurse = minShiftsPerNurse;
    } else {
      maxShiftsPerNurse = minShiftsPerNurse + 1;
    }
    for (int n : allNurses) {
      LinearExprBuilder numShiftsWorked = LinearExpr.newBuilder();
      for (int d : allDays) {
        for (int s : allShifts) {
          numShiftsWorked.add(shifts[n][d][s]);
        }
      }
      model.addLinearConstraint(numShiftsWorked, minShiftsPerNurse, maxShiftsPerNurse);
    }

    LinearExprBuilder obj = LinearExpr.newBuilder();
    for (int n : allNurses) {
      for (int d : allDays) {
        for (int s : allShifts) {
          obj.addTerm(shifts[n][d][s], shiftRequests[n][d][s]);
        }
      }
    }
    model.maximize(obj);

    // Creates a solver and solves the model.
    CpSolver solver = new CpSolver();
    CpSolverStatus status = solver.solve(model);

    if (status == CpSolverStatus.OPTIMAL || status == CpSolverStatus.FEASIBLE) {
      System.out.printf("Solution:%n");
      for (int d : allDays) {
        System.out.printf("Day %d%n", d);
        for (int n : allNurses) {
          for (int s : allShifts) {
            if (solver.booleanValue(shifts[n][d][s])) {
              if (shiftRequests[n][d][s] == 1) {
                System.out.printf("  Nurse %d works shift %d (requested).%n", n, s);
              } else {
                System.out.printf("  Nurse %d works shift %d (not requested).%n", n, s);
              }
            }
          }
        }
      }
      System.out.printf("Number of shift requests met = %f (out of %d)%n", solver.objectiveValue(),
          numNurses * minShiftsPerNurse);
    } else {
      System.out.printf("No optimal solution found !");
    }
    // Statistics.
    System.out.println("Statistics");
    System.out.printf("  conflicts: %d%n", solver.numConflicts());
    System.out.printf("  branches : %d%n", solver.numBranches());
    System.out.printf("  wall time: %f s%n", solver.wallTime());
  }

  private ScheduleRequestsSat() {}
}

C#‎

using System;
using System.Collections.Generic;
using System.Linq;
using Google.OrTools.Sat;

public class ScheduleRequestsSat
{
    public static void Main(String[] args)
    {
        const int numNurses = 5;
        const int numDays = 7;
        const int numShifts = 3;

        int[] allNurses = Enumerable.Range(0, numNurses).ToArray();
        int[] allDays = Enumerable.Range(0, numDays).ToArray();
        int[] allShifts = Enumerable.Range(0, numShifts).ToArray();

        int[,,] shiftRequests = new int[,,] {
            {
                { 0, 0, 1 },
                { 0, 0, 0 },
                { 0, 0, 0 },
                { 0, 0, 0 },
                { 0, 0, 1 },
                { 0, 1, 0 },
                { 0, 0, 1 },
            },
            {
                { 0, 0, 0 },
                { 0, 0, 0 },
                { 0, 1, 0 },
                { 0, 1, 0 },
                { 1, 0, 0 },
                { 0, 0, 0 },
                { 0, 0, 1 },
            },
            {
                { 0, 1, 0 },
                { 0, 1, 0 },
                { 0, 0, 0 },
                { 1, 0, 0 },
                { 0, 0, 0 },
                { 0, 1, 0 },
                { 0, 0, 0 },
            },
            {
                { 0, 0, 1 },
                { 0, 0, 0 },
                { 1, 0, 0 },
                { 0, 1, 0 },
                { 0, 0, 0 },
                { 1, 0, 0 },
                { 0, 0, 0 },
            },
            {
                { 0, 0, 0 },
                { 0, 0, 1 },
                { 0, 1, 0 },
                { 0, 0, 0 },
                { 1, 0, 0 },
                { 0, 1, 0 },
                { 0, 0, 0 },
            },
        };

        // Creates the model.
        CpModel model = new CpModel();

        // Creates shift variables.
        // shifts[(n, d, s)]: nurse 'n' works shift 's' on day 'd'.
        Dictionary<Tuple<int, int, int>, IntVar> shifts = new Dictionary<Tuple<int, int, int>, IntVar>();
        foreach (int n in allNurses)
        {
            foreach (int d in allDays)
            {
                foreach (int s in allShifts)
                {
                    shifts.Add(Tuple.Create(n, d, s), model.NewBoolVar($"shifts_n{n}d{d}s{s}"));
                }
            }
        }

        // Each shift is assigned to exactly one nurse in the schedule period.
        foreach (int d in allDays)
        {
            foreach (int s in allShifts)
            {
                IntVar[] x = new IntVar[numNurses];
                foreach (int n in allNurses)
                {
                    var key = Tuple.Create(n, d, s);
                    x[n] = shifts[key];
                }
                model.Add(LinearExpr.Sum(x) == 1);
            }
        }

        // Each nurse works at most one shift per day.
        foreach (int n in allNurses)
        {
            foreach (int d in allDays)
            {
                IntVar[] x = new IntVar[numShifts];
                foreach (int s in allShifts)
                {
                    var key = Tuple.Create(n, d, s);
                    x[s] = shifts[key];
                }
                model.Add(LinearExpr.Sum(x) <= 1);
            }
        }

        // Try to distribute the shifts evenly, so that each nurse works
        // minShiftsPerNurse shifts. If this is not possible, because the total
        // number of shifts is not divisible by the number of nurses, some nurses will
        // be assigned one more shift.
        int minShiftsPerNurse = (numShifts * numDays) / numNurses;
        int maxShiftsPerNurse;
        if ((numShifts * numDays) % numNurses == 0)
        {
            maxShiftsPerNurse = minShiftsPerNurse;
        }
        else
        {
            maxShiftsPerNurse = minShiftsPerNurse + 1;
        }
        foreach (int n in allNurses)
        {
            IntVar[] numShiftsWorked = new IntVar[numDays * numShifts];
            foreach (int d in allDays)
            {
                foreach (int s in allShifts)
                {
                    var key = Tuple.Create(n, d, s);
                    numShiftsWorked[d * numShifts + s] = shifts[key];
                }
            }
            model.AddLinearConstraint(LinearExpr.Sum(numShiftsWorked), minShiftsPerNurse, maxShiftsPerNurse);
        }

        IntVar[] flatShifts = new IntVar[numNurses * numDays * numShifts];
        int[] flatShiftRequests = new int[numNurses * numDays * numShifts];
        foreach (int n in allNurses)
        {
            foreach (int d in allDays)
            {
                foreach (int s in allShifts)
                {
                    var key = Tuple.Create(n, d, s);
                    flatShifts[n * numDays * numShifts + d * numShifts + s] = shifts[key];
                    flatShiftRequests[n * numDays * numShifts + d * numShifts + s] = shiftRequests[n, d, s];
                }
            }
        }
        model.Maximize(LinearExpr.WeightedSum(flatShifts, flatShiftRequests));

        // Solve
        CpSolver solver = new CpSolver();
        CpSolverStatus status = solver.Solve(model);
        Console.WriteLine($"Solve status: {status}");

        if (status == CpSolverStatus.Optimal || status == CpSolverStatus.Feasible)
        {
            Console.WriteLine("Solution:");
            foreach (int d in allDays)
            {
                Console.WriteLine($"Day {d}");
                foreach (int n in allNurses)
                {
                    bool isWorking = false;
                    foreach (int s in allShifts)
                    {
                        var key = Tuple.Create(n, d, s);
                        if (solver.Value(shifts[key]) == 1L)
                        {
                            if (shiftRequests[n, d, s] == 1)
                            {
                                Console.WriteLine($"  Nurse {n} work shift {s} (requested).");
                            }
                            else
                            {
                                Console.WriteLine($"  Nurse {n} work shift {s} (not requested).");
                            }
                        }
                    }
                }
            }
            Console.WriteLine(
                $"Number of shift requests met = {solver.ObjectiveValue} (out of {numNurses * minShiftsPerNurse}).");
        }
        else
        {
            Console.WriteLine("No solution found.");
        }

        Console.WriteLine("Statistics");
        Console.WriteLine($"  conflicts: {solver.NumConflicts()}");
        Console.WriteLine($"  branches : {solver.NumBranches()}");
        Console.WriteLine($"  wall time: {solver.WallTime()}s");
    }
}