min. maliyet akışı çözücüyü kullanarak bir anahtar kelimenin özel .
Aslına bakılırsa minimum maliyet akışı genellikle bir çözümü MIP veya MIP’den daha hızlı CP-SAT çözücü. Ancak MIP ve CP-SAT, daha büyük sınıfları çözmek için Bu nedenle çoğu durumda MIP veya CP-SAT en iyi seçenektir.
Aşağıdaki bölümlerde, aşağıdaki sorunları çözen Python programları sunulmaktadır min. maliyet akışı çözücüyü kullanarak atama problemleri:
- Minimal bir doğrusal atama örneği.
- Çalışan ekipleri ile ilgili bir atama sorunu.
Doğrusal atama örneği
Bu bölümde, örneğin nasıl çözüleceği gösterilmektedir. Doğrusal Ödev Çözücü, dakika olarak soruna neden olabilir.
Kitaplıkları içe aktarma
Aşağıdaki kod, gerekli kitaplığı içe aktarır.
Python
from ortools.graph.python import min_cost_flow
C++
#include <cstdint> #include <vector> #include "ortools/graph/min_cost_flow.h"
Java
import com.google.ortools.Loader; import com.google.ortools.graph.MinCostFlow; import com.google.ortools.graph.MinCostFlowBase;
C#
using System; using Google.OrTools.Graph;
Çözücüyü tanımlama
Aşağıdaki kod minimum maliyet akışı çözücüyü oluşturur.
Python
# Instantiate a SimpleMinCostFlow solver. smcf = min_cost_flow.SimpleMinCostFlow()
C++
// Instantiate a SimpleMinCostFlow solver. SimpleMinCostFlow min_cost_flow;
Java
// Instantiate a SimpleMinCostFlow solver. MinCostFlow minCostFlow = new MinCostFlow();
C#
// Instantiate a SimpleMinCostFlow solver. MinCostFlow minCostFlow = new MinCostFlow();
Verileri oluşturma
Problemin akış diyagramı maliyete ait iki taraflı grafikten oluşur matris için (bkz. ödevlere genel bakış farklı bir örnek) ekleyin.
Veriler, başlangıç düğümlerine karşılık gelen aşağıdaki dört diziyi içerir: kapasiteleri, maliyetleri ve maliyetleri tanımlayın. Her bir dizinin uzunluğu grafikteki yay sayısını gösterir.
Python
# Define the directed graph for the flow. start_nodes = ( [0, 0, 0, 0] + [1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4] + [5, 6, 7, 8] ) end_nodes = ( [1, 2, 3, 4] + [5, 6, 7, 8, 5, 6, 7, 8, 5, 6, 7, 8, 5, 6, 7, 8] + [9, 9, 9, 9] ) capacities = ( [1, 1, 1, 1] + [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1] + [1, 1, 1, 1] ) costs = ( [0, 0, 0, 0] + [90, 76, 75, 70, 35, 85, 55, 65, 125, 95, 90, 105, 45, 110, 95, 115] + [0, 0, 0, 0] ) source = 0 sink = 9 tasks = 4 supplies = [tasks, 0, 0, 0, 0, 0, 0, 0, 0, -tasks]
C++
// Define four parallel arrays: sources, destinations, capacities, // and unit costs between each pair. For instance, the arc from node 0 // to node 1 has a capacity of 15. const std::vector<int64_t> start_nodes = {0, 0, 0, 0, 1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4, 5, 6, 7, 8}; const std::vector<int64_t> end_nodes = {1, 2, 3, 4, 5, 6, 7, 8, 5, 6, 7, 8, 5, 6, 7, 8, 5, 6, 7, 8, 9, 9, 9, 9}; const std::vector<int64_t> capacities = {1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1}; const std::vector<int64_t> unit_costs = {0, 0, 0, 0, 90, 76, 75, 70, 35, 85, 55, 65, 125, 95, 90, 105, 45, 110, 95, 115, 0, 0, 0, 0}; const int64_t source = 0; const int64_t sink = 9; const int64_t tasks = 4; // Define an array of supplies at each node. const std::vector<int64_t> supplies = {tasks, 0, 0, 0, 0, 0, 0, 0, 0, -tasks};
Java
// Define four parallel arrays: sources, destinations, capacities, and unit costs // between each pair. int[] startNodes = new int[] {0, 0, 0, 0, 1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4, 5, 6, 7, 8}; int[] endNodes = new int[] {1, 2, 3, 4, 5, 6, 7, 8, 5, 6, 7, 8, 5, 6, 7, 8, 5, 6, 7, 8, 9, 9, 9, 9}; int[] capacities = new int[] {1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1}; int[] unitCosts = new int[] { 0, 0, 0, 0, 90, 76, 75, 70, 35, 85, 55, 65, 125, 95, 90, 105, 45, 110, 95, 115, 0, 0, 0, 0}; int source = 0; int sink = 9; int tasks = 4; // Define an array of supplies at each node. int[] supplies = new int[] {tasks, 0, 0, 0, 0, 0, 0, 0, 0, -tasks};
C#
// Define four parallel arrays: sources, destinations, capacities, and unit costs // between each pair. int[] startNodes = { 0, 0, 0, 0, 1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4, 5, 6, 7, 8 }; int[] endNodes = { 1, 2, 3, 4, 5, 6, 7, 8, 5, 6, 7, 8, 5, 6, 7, 8, 5, 6, 7, 8, 9, 9, 9, 9 }; int[] capacities = { 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 }; int[] unitCosts = { 0, 0, 0, 0, 90, 76, 75, 70, 35, 85, 55, 65, 125, 95, 90, 105, 45, 110, 95, 115, 0, 0, 0, 0 }; int source = 0; int sink = 9; int tasks = 4; // Define an array of supplies at each node. int[] supplies = { tasks, 0, 0, 0, 0, 0, 0, 0, 0, -tasks };
Verilerin nasıl ayarlandığını netleştirmek amacıyla her dizi üçe bölünür alt diziler:
- İlk dizi, kaynaktan dışarı çıkan yaylara karşılık gelir.
- İkinci dizi, çalışanlar ve görevler arasındaki yaylara karşılık gelir.
costs
için bu yalnızca maliyet matrisi (doğrusal atama çözücü tarafından kullanılır) bir vektöre düzleştirilir. - Üçüncü dizi, lavaboya giden yaylara karşılık gelir.
Veriler, her birinde tedariki veren supplies
vektörünü de içerir.
düğüm.
Minimum maliyet akışı problemi bir atama sorununu nasıl temsil eder?
Yukarıdaki minimum maliyet akışı problemi, bir atama sorununu nasıl temsil eder? İlk olarak, Her bir yay kapasitesi 1 olduğundan, kaynakta 4'ün arzı her bir yay kuvvetini artırır çalışanlarına giden akıştaki akışın 1'dir.
Daha sonra, akışa eşittir-çıkış koşulu, her çalışandan akışı zorlar olacaktır. Çözücü, mümkünse bu akışı minimum maliyete yönlendirir. oluşan bir yay vardır. Ancak çözücü, akıştan gelen akışı tek bir göreve atıyor. Gerektiği takdirde, toplam maliyet bu göreve tek bir yayın boyunca gönderilemeyen kapasite 1’dir. Bu, çözücünün bir görevi yalnızca tek bir çalışana atayabileceği anlamına gelir. netleştirmelerini de sağlar.
Son olarak, "içine akış eşittir"-çıkış koşulu, her görevin bir her görev bir çalışan tarafından yürütülür.
Grafik ve kısıtlamaları oluşturma
Aşağıdaki kod, grafiği ve kısıtlamaları oluşturur.
Python
# Add each arc. for i in range(len(start_nodes)): smcf.add_arc_with_capacity_and_unit_cost( start_nodes[i], end_nodes[i], capacities[i], costs[i] ) # Add node supplies. for i in range(len(supplies)): smcf.set_node_supply(i, supplies[i])
C++
// Add each arc. for (int i = 0; i < start_nodes.size(); ++i) { int arc = min_cost_flow.AddArcWithCapacityAndUnitCost( start_nodes[i], end_nodes[i], capacities[i], unit_costs[i]); if (arc != i) LOG(FATAL) << "Internal error"; } // Add node supplies. for (int i = 0; i < supplies.size(); ++i) { min_cost_flow.SetNodeSupply(i, supplies[i]); }
Java
// Add each arc. for (int i = 0; i < startNodes.length; ++i) { int arc = minCostFlow.addArcWithCapacityAndUnitCost( startNodes[i], endNodes[i], capacities[i], unitCosts[i]); if (arc != i) { throw new Exception("Internal error"); } } // Add node supplies. for (int i = 0; i < supplies.length; ++i) { minCostFlow.setNodeSupply(i, supplies[i]); }
C#
// Add each arc. for (int i = 0; i < startNodes.Length; ++i) { int arc = minCostFlow.AddArcWithCapacityAndUnitCost(startNodes[i], endNodes[i], capacities[i], unitCosts[i]); if (arc != i) throw new Exception("Internal error"); } // Add node supplies. for (int i = 0; i < supplies.Length; ++i) { minCostFlow.SetNodeSupply(i, supplies[i]); }
Çözücüyü çağır
Aşağıdaki kod çözücüyü çağırır ve çözümü gösterir.
Python
# Find the minimum cost flow between node 0 and node 10. status = smcf.solve()
C++
// Find the min cost flow. int status = min_cost_flow.Solve();
Java
// Find the min cost flow. MinCostFlowBase.Status status = minCostFlow.solve();
C#
// Find the min cost flow. MinCostFlow.Status status = minCostFlow.Solve();
Çözüm, çalışanlar ile onların birbirlerine atanan görevlerin 1'in akışını sağlar. (Kaynağa veya havuza bağlı yaylar gerekir.)
Program, her bir yayını kontrol ederek akış 1'in olup olmadığına bakar.
Yayının Tail
(başlangıç düğümü) ve Head
(bitiş düğümü) için,
ve göreve hazırlar.
Programın çıkışı
Python
if status == smcf.OPTIMAL: print("Total cost = ", smcf.optimal_cost()) print() for arc in range(smcf.num_arcs()): # Can ignore arcs leading out of source or into sink. if smcf.tail(arc) != source and smcf.head(arc) != sink: # Arcs in the solution have a flow value of 1. Their start and end nodes # give an assignment of worker to task. if smcf.flow(arc) > 0: print( "Worker %d assigned to task %d. Cost = %d" % (smcf.tail(arc), smcf.head(arc), smcf.unit_cost(arc)) ) else: print("There was an issue with the min cost flow input.") print(f"Status: {status}")
C++
if (status == MinCostFlow::OPTIMAL) { LOG(INFO) << "Total cost: " << min_cost_flow.OptimalCost(); LOG(INFO) << ""; for (std::size_t i = 0; i < min_cost_flow.NumArcs(); ++i) { // Can ignore arcs leading out of source or into sink. if (min_cost_flow.Tail(i) != source && min_cost_flow.Head(i) != sink) { // Arcs in the solution have a flow value of 1. Their start and end // nodes give an assignment of worker to task. if (min_cost_flow.Flow(i) > 0) { LOG(INFO) << "Worker " << min_cost_flow.Tail(i) << " assigned to task " << min_cost_flow.Head(i) << " Cost: " << min_cost_flow.UnitCost(i); } } } } else { LOG(INFO) << "Solving the min cost flow problem failed."; LOG(INFO) << "Solver status: " << status; }
Java
if (status == MinCostFlow.Status.OPTIMAL) { System.out.println("Total cost: " + minCostFlow.getOptimalCost()); System.out.println(); for (int i = 0; i < minCostFlow.getNumArcs(); ++i) { // Can ignore arcs leading out of source or into sink. if (minCostFlow.getTail(i) != source && minCostFlow.getHead(i) != sink) { // Arcs in the solution have a flow value of 1. Their start and end nodes // give an assignment of worker to task. if (minCostFlow.getFlow(i) > 0) { System.out.println("Worker " + minCostFlow.getTail(i) + " assigned to task " + minCostFlow.getHead(i) + " Cost: " + minCostFlow.getUnitCost(i)); } } } } else { System.out.println("Solving the min cost flow problem failed."); System.out.println("Solver status: " + status); }
C#
if (status == MinCostFlow.Status.OPTIMAL) { Console.WriteLine("Total cost: " + minCostFlow.OptimalCost()); Console.WriteLine(""); for (int i = 0; i < minCostFlow.NumArcs(); ++i) { // Can ignore arcs leading out of source or into sink. if (minCostFlow.Tail(i) != source && minCostFlow.Head(i) != sink) { // Arcs in the solution have a flow value of 1. Their start and end nodes // give an assignment of worker to task. if (minCostFlow.Flow(i) > 0) { Console.WriteLine("Worker " + minCostFlow.Tail(i) + " assigned to task " + minCostFlow.Head(i) + " Cost: " + minCostFlow.UnitCost(i)); } } } } else { Console.WriteLine("Solving the min cost flow problem failed."); Console.WriteLine("Solver status: " + status); }
İşte programın çıktısı.
Total cost = 265 Worker 1 assigned to task 8. Cost = 70 Worker 2 assigned to task 7. Cost = 55 Worker 3 assigned to task 6. Cost = 95 Worker 4 assigned to task 5. Cost = 45 Time = 0.000245 seconds
Sonuç, doğrusal ödev çözücü (farklı sayısı ile maliyetleri) hesaplar. Doğrusal ödev çözücü biraz daha hızlıdır daha fazla değer: 0,000458 saniye yerine 0,000147 saniye.
Programın tamamı
Programın tamamı aşağıda gösterilmektedir.
Python
"""Linear assignment example.""" from ortools.graph.python import min_cost_flow def main(): """Solving an Assignment Problem with MinCostFlow.""" # Instantiate a SimpleMinCostFlow solver. smcf = min_cost_flow.SimpleMinCostFlow() # Define the directed graph for the flow. start_nodes = ( [0, 0, 0, 0] + [1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4] + [5, 6, 7, 8] ) end_nodes = ( [1, 2, 3, 4] + [5, 6, 7, 8, 5, 6, 7, 8, 5, 6, 7, 8, 5, 6, 7, 8] + [9, 9, 9, 9] ) capacities = ( [1, 1, 1, 1] + [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1] + [1, 1, 1, 1] ) costs = ( [0, 0, 0, 0] + [90, 76, 75, 70, 35, 85, 55, 65, 125, 95, 90, 105, 45, 110, 95, 115] + [0, 0, 0, 0] ) source = 0 sink = 9 tasks = 4 supplies = [tasks, 0, 0, 0, 0, 0, 0, 0, 0, -tasks] # Add each arc. for i in range(len(start_nodes)): smcf.add_arc_with_capacity_and_unit_cost( start_nodes[i], end_nodes[i], capacities[i], costs[i] ) # Add node supplies. for i in range(len(supplies)): smcf.set_node_supply(i, supplies[i]) # Find the minimum cost flow between node 0 and node 10. status = smcf.solve() if status == smcf.OPTIMAL: print("Total cost = ", smcf.optimal_cost()) print() for arc in range(smcf.num_arcs()): # Can ignore arcs leading out of source or into sink. if smcf.tail(arc) != source and smcf.head(arc) != sink: # Arcs in the solution have a flow value of 1. Their start and end nodes # give an assignment of worker to task. if smcf.flow(arc) > 0: print( "Worker %d assigned to task %d. Cost = %d" % (smcf.tail(arc), smcf.head(arc), smcf.unit_cost(arc)) ) else: print("There was an issue with the min cost flow input.") print(f"Status: {status}") if __name__ == "__main__": main()
C++
#include <cstdint> #include <vector> #include "ortools/graph/min_cost_flow.h" namespace operations_research { // MinCostFlow simple interface example. void AssignmentMinFlow() { // Instantiate a SimpleMinCostFlow solver. SimpleMinCostFlow min_cost_flow; // Define four parallel arrays: sources, destinations, capacities, // and unit costs between each pair. For instance, the arc from node 0 // to node 1 has a capacity of 15. const std::vector<int64_t> start_nodes = {0, 0, 0, 0, 1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4, 5, 6, 7, 8}; const std::vector<int64_t> end_nodes = {1, 2, 3, 4, 5, 6, 7, 8, 5, 6, 7, 8, 5, 6, 7, 8, 5, 6, 7, 8, 9, 9, 9, 9}; const std::vector<int64_t> capacities = {1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1}; const std::vector<int64_t> unit_costs = {0, 0, 0, 0, 90, 76, 75, 70, 35, 85, 55, 65, 125, 95, 90, 105, 45, 110, 95, 115, 0, 0, 0, 0}; const int64_t source = 0; const int64_t sink = 9; const int64_t tasks = 4; // Define an array of supplies at each node. const std::vector<int64_t> supplies = {tasks, 0, 0, 0, 0, 0, 0, 0, 0, -tasks}; // Add each arc. for (int i = 0; i < start_nodes.size(); ++i) { int arc = min_cost_flow.AddArcWithCapacityAndUnitCost( start_nodes[i], end_nodes[i], capacities[i], unit_costs[i]); if (arc != i) LOG(FATAL) << "Internal error"; } // Add node supplies. for (int i = 0; i < supplies.size(); ++i) { min_cost_flow.SetNodeSupply(i, supplies[i]); } // Find the min cost flow. int status = min_cost_flow.Solve(); if (status == MinCostFlow::OPTIMAL) { LOG(INFO) << "Total cost: " << min_cost_flow.OptimalCost(); LOG(INFO) << ""; for (std::size_t i = 0; i < min_cost_flow.NumArcs(); ++i) { // Can ignore arcs leading out of source or into sink. if (min_cost_flow.Tail(i) != source && min_cost_flow.Head(i) != sink) { // Arcs in the solution have a flow value of 1. Their start and end // nodes give an assignment of worker to task. if (min_cost_flow.Flow(i) > 0) { LOG(INFO) << "Worker " << min_cost_flow.Tail(i) << " assigned to task " << min_cost_flow.Head(i) << " Cost: " << min_cost_flow.UnitCost(i); } } } } else { LOG(INFO) << "Solving the min cost flow problem failed."; LOG(INFO) << "Solver status: " << status; } } } // namespace operations_research int main() { operations_research::AssignmentMinFlow(); return EXIT_SUCCESS; }
Java
package com.google.ortools.graph.samples; import com.google.ortools.Loader; import com.google.ortools.graph.MinCostFlow; import com.google.ortools.graph.MinCostFlowBase; /** Minimal Assignment Min Flow. */ public class AssignmentMinFlow { public static void main(String[] args) throws Exception { Loader.loadNativeLibraries(); // Instantiate a SimpleMinCostFlow solver. MinCostFlow minCostFlow = new MinCostFlow(); // Define four parallel arrays: sources, destinations, capacities, and unit costs // between each pair. int[] startNodes = new int[] {0, 0, 0, 0, 1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4, 5, 6, 7, 8}; int[] endNodes = new int[] {1, 2, 3, 4, 5, 6, 7, 8, 5, 6, 7, 8, 5, 6, 7, 8, 5, 6, 7, 8, 9, 9, 9, 9}; int[] capacities = new int[] {1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1}; int[] unitCosts = new int[] { 0, 0, 0, 0, 90, 76, 75, 70, 35, 85, 55, 65, 125, 95, 90, 105, 45, 110, 95, 115, 0, 0, 0, 0}; int source = 0; int sink = 9; int tasks = 4; // Define an array of supplies at each node. int[] supplies = new int[] {tasks, 0, 0, 0, 0, 0, 0, 0, 0, -tasks}; // Add each arc. for (int i = 0; i < startNodes.length; ++i) { int arc = minCostFlow.addArcWithCapacityAndUnitCost( startNodes[i], endNodes[i], capacities[i], unitCosts[i]); if (arc != i) { throw new Exception("Internal error"); } } // Add node supplies. for (int i = 0; i < supplies.length; ++i) { minCostFlow.setNodeSupply(i, supplies[i]); } // Find the min cost flow. MinCostFlowBase.Status status = minCostFlow.solve(); if (status == MinCostFlow.Status.OPTIMAL) { System.out.println("Total cost: " + minCostFlow.getOptimalCost()); System.out.println(); for (int i = 0; i < minCostFlow.getNumArcs(); ++i) { // Can ignore arcs leading out of source or into sink. if (minCostFlow.getTail(i) != source && minCostFlow.getHead(i) != sink) { // Arcs in the solution have a flow value of 1. Their start and end nodes // give an assignment of worker to task. if (minCostFlow.getFlow(i) > 0) { System.out.println("Worker " + minCostFlow.getTail(i) + " assigned to task " + minCostFlow.getHead(i) + " Cost: " + minCostFlow.getUnitCost(i)); } } } } else { System.out.println("Solving the min cost flow problem failed."); System.out.println("Solver status: " + status); } } private AssignmentMinFlow() {} }
C#
using System; using Google.OrTools.Graph; public class AssignmentMinFlow { static void Main() { // Instantiate a SimpleMinCostFlow solver. MinCostFlow minCostFlow = new MinCostFlow(); // Define four parallel arrays: sources, destinations, capacities, and unit costs // between each pair. int[] startNodes = { 0, 0, 0, 0, 1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4, 5, 6, 7, 8 }; int[] endNodes = { 1, 2, 3, 4, 5, 6, 7, 8, 5, 6, 7, 8, 5, 6, 7, 8, 5, 6, 7, 8, 9, 9, 9, 9 }; int[] capacities = { 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 }; int[] unitCosts = { 0, 0, 0, 0, 90, 76, 75, 70, 35, 85, 55, 65, 125, 95, 90, 105, 45, 110, 95, 115, 0, 0, 0, 0 }; int source = 0; int sink = 9; int tasks = 4; // Define an array of supplies at each node. int[] supplies = { tasks, 0, 0, 0, 0, 0, 0, 0, 0, -tasks }; // Add each arc. for (int i = 0; i < startNodes.Length; ++i) { int arc = minCostFlow.AddArcWithCapacityAndUnitCost(startNodes[i], endNodes[i], capacities[i], unitCosts[i]); if (arc != i) throw new Exception("Internal error"); } // Add node supplies. for (int i = 0; i < supplies.Length; ++i) { minCostFlow.SetNodeSupply(i, supplies[i]); } // Find the min cost flow. MinCostFlow.Status status = minCostFlow.Solve(); if (status == MinCostFlow.Status.OPTIMAL) { Console.WriteLine("Total cost: " + minCostFlow.OptimalCost()); Console.WriteLine(""); for (int i = 0; i < minCostFlow.NumArcs(); ++i) { // Can ignore arcs leading out of source or into sink. if (minCostFlow.Tail(i) != source && minCostFlow.Head(i) != sink) { // Arcs in the solution have a flow value of 1. Their start and end nodes // give an assignment of worker to task. if (minCostFlow.Flow(i) > 0) { Console.WriteLine("Worker " + minCostFlow.Tail(i) + " assigned to task " + minCostFlow.Head(i) + " Cost: " + minCostFlow.UnitCost(i)); } } } } else { Console.WriteLine("Solving the min cost flow problem failed."); Console.WriteLine("Solver status: " + status); } } }
Çalışan ekipleriyle atama
Bu bölümde, daha genel bir ödev sorunu açıklanmaktadır. Bu problemde altı çalışanlar iki ekibe bölünür. Buradaki sorun, büyük çaplı müşterilere iş yükünün ekipler arasında eşit bir şekilde dengelenmesi için, her ekip iki görev yerine getirir.
Bu soruna yönelik bir MIP çözücü çözümü için bkz. Çalışan Ekipleriyle Ödevler.
Aşağıdaki bölümlerde problemi çözmek için minimum maliyet akışı çözücü.
Kitaplıkları içe aktarma
Aşağıdaki kod, gerekli kitaplığı içe aktarır.
Python
from ortools.graph.python import min_cost_flow
C++
#include <cstdint> #include <vector> #include "ortools/graph/min_cost_flow.h"
Java
import com.google.ortools.Loader; import com.google.ortools.graph.MinCostFlow; import com.google.ortools.graph.MinCostFlowBase;
C#
using System; using Google.OrTools.Graph;
Çözücüyü tanımlama
Aşağıdaki kod minimum maliyet akışı çözücüyü oluşturur.
Python
smcf = min_cost_flow.SimpleMinCostFlow()
C++
// Instantiate a SimpleMinCostFlow solver. SimpleMinCostFlow min_cost_flow;
Java
// Instantiate a SimpleMinCostFlow solver. MinCostFlow minCostFlow = new MinCostFlow();
C#
// Instantiate a SimpleMinCostFlow solver. MinCostFlow minCostFlow = new MinCostFlow();
Verileri oluşturma
Aşağıdaki kod, program için veri oluşturur.
Python
# Define the directed graph for the flow. team_a = [1, 3, 5] team_b = [2, 4, 6] start_nodes = ( # fmt: off [0, 0] + [11, 11, 11] + [12, 12, 12] + [1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 5, 6, 6, 6, 6] + [7, 8, 9, 10] # fmt: on ) end_nodes = ( # fmt: off [11, 12] + team_a + team_b + [7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10] + [13, 13, 13, 13] # fmt: on ) capacities = ( # fmt: off [2, 2] + [1, 1, 1] + [1, 1, 1] + [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1] + [1, 1, 1, 1] # fmt: on ) costs = ( # fmt: off [0, 0] + [0, 0, 0] + [0, 0, 0] + [90, 76, 75, 70, 35, 85, 55, 65, 125, 95, 90, 105, 45, 110, 95, 115, 60, 105, 80, 75, 45, 65, 110, 95] + [0, 0, 0, 0] # fmt: on ) source = 0 sink = 13 tasks = 4 # Define an array of supplies at each node. supplies = [tasks, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -tasks]
C++
// Define the directed graph for the flow. const std::vector<int64_t> team_A = {1, 3, 5}; const std::vector<int64_t> team_B = {2, 4, 6}; const std::vector<int64_t> start_nodes = { 0, 0, 11, 11, 11, 12, 12, 12, 1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 5, 6, 6, 6, 6, 7, 8, 9, 10}; const std::vector<int64_t> end_nodes = { 11, 12, 1, 3, 5, 2, 4, 6, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 13, 13, 13, 13}; const std::vector<int64_t> capacities = {2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1}; const std::vector<int64_t> unit_costs = { 0, 0, 0, 0, 0, 0, 0, 0, 90, 76, 75, 70, 35, 85, 55, 65, 125, 95, 90, 105, 45, 110, 95, 115, 60, 105, 80, 75, 45, 65, 110, 95, 0, 0, 0, 0}; const int64_t source = 0; const int64_t sink = 13; const int64_t tasks = 4; // Define an array of supplies at each node. const std::vector<int64_t> supplies = {tasks, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -tasks};
Java
// Define the directed graph for the flow. // int[] teamA = new int[] {1, 3, 5}; // int[] teamB = new int[] {2, 4, 6}; int[] startNodes = new int[] {0, 0, 11, 11, 11, 12, 12, 12, 1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 5, 6, 6, 6, 6, 7, 8, 9, 10}; int[] endNodes = new int[] {11, 12, 1, 3, 5, 2, 4, 6, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 13, 13, 13, 13}; int[] capacities = new int[] {2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1}; int[] unitCosts = new int[] {0, 0, 0, 0, 0, 0, 0, 0, 90, 76, 75, 70, 35, 85, 55, 65, 125, 95, 90, 105, 45, 110, 95, 115, 60, 105, 80, 75, 45, 65, 110, 95, 0, 0, 0, 0}; int source = 0; int sink = 13; int tasks = 4; // Define an array of supplies at each node. int[] supplies = new int[] {tasks, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -tasks};
C#
// Define the directed graph for the flow. int[] teamA = { 1, 3, 5 }; int[] teamB = { 2, 4, 6 }; // Define four parallel arrays: sources, destinations, capacities, and unit costs // between each pair. int[] startNodes = { 0, 0, 11, 11, 11, 12, 12, 12, 1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 5, 6, 6, 6, 6, 7, 8, 9, 10 }; int[] endNodes = { 11, 12, 1, 3, 5, 2, 4, 6, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 13, 13, 13, 13 }; int[] capacities = { 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 }; int[] unitCosts = { 0, 0, 0, 0, 0, 0, 0, 0, 90, 76, 75, 70, 35, 85, 55, 65, 125, 95, 90, 105, 45, 110, 95, 115, 60, 105, 80, 75, 45, 65, 110, 95, 0, 0, 0, 0 }; int source = 0; int sink = 13; int tasks = 4; // Define an array of supplies at each node. int[] supplies = { tasks, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -tasks };
Çalışanlar, 1 - 6 arasındaki düğümlere karşılık gelir. A Ekibi ise 1, 3 ve 5 numaralı çalışanlardan, B ekibi ise 2, 4 ve 6. çalışanlardan oluşur. Görevler 7’den 10’a kadar numaralandırılmış.
Kaynak ve çalışanlar arasında 11 ve 12 numaralı iki yeni düğüm vardır. Düğüm 11 Düğüm 12, ekibin A ekibinin düğümlerine bağlanır ve Düğüm 12 ya da 1. kapasite yayları görünür. Aşağıdaki grafikte yalnızca kaynaktan çalışanlara giden düğümler ve yaylar gösterilmektedir.
İş yükünü dengelemenin püf noktası, kaynak 0'ın 11. düğümlere bağlı olmasıdır. ve 2. kapasite yaylı 12'dir. Bu, 11. ve 12. düğümlerin (ve dolayısıyla (A ve B ekiplerinde) maksimum 2 akış olabilir. Sonuç olarak, her ekip görevden en fazla iki tanesini gerçekleştirebilir.
Kısıtlamaları oluşturma
Python
# Add each arc. for i in range(0, len(start_nodes)): smcf.add_arc_with_capacity_and_unit_cost( start_nodes[i], end_nodes[i], capacities[i], costs[i] ) # Add node supplies. for i in range(0, len(supplies)): smcf.set_node_supply(i, supplies[i])
C++
// Add each arc. for (int i = 0; i < start_nodes.size(); ++i) { int arc = min_cost_flow.AddArcWithCapacityAndUnitCost( start_nodes[i], end_nodes[i], capacities[i], unit_costs[i]); if (arc != i) LOG(FATAL) << "Internal error"; } // Add node supplies. for (int i = 0; i < supplies.size(); ++i) { min_cost_flow.SetNodeSupply(i, supplies[i]); }
Java
// Add each arc. for (int i = 0; i < startNodes.length; ++i) { int arc = minCostFlow.addArcWithCapacityAndUnitCost( startNodes[i], endNodes[i], capacities[i], unitCosts[i]); if (arc != i) { throw new Exception("Internal error"); } } // Add node supplies. for (int i = 0; i < supplies.length; ++i) { minCostFlow.setNodeSupply(i, supplies[i]); }
C#
// Add each arc. for (int i = 0; i < startNodes.Length; ++i) { int arc = minCostFlow.AddArcWithCapacityAndUnitCost(startNodes[i], endNodes[i], capacities[i], unitCosts[i]); if (arc != i) throw new Exception("Internal error"); } // Add node supplies. for (int i = 0; i < supplies.Length; ++i) { minCostFlow.SetNodeSupply(i, supplies[i]); }
Çözücüyü çağır
Python
# Find the minimum cost flow between node 0 and node 10. status = smcf.solve()
C++
// Find the min cost flow. int status = min_cost_flow.Solve();
Java
// Find the min cost flow. MinCostFlowBase.Status status = minCostFlow.solve();
C#
// Find the min cost flow. MinCostFlow.Status status = minCostFlow.Solve();
Programın çıkışı
Python
if status == smcf.OPTIMAL: print("Total cost = ", smcf.optimal_cost()) print() for arc in range(smcf.num_arcs()): # Can ignore arcs leading out of source or intermediate, or into sink. if ( smcf.tail(arc) != source and smcf.tail(arc) != 11 and smcf.tail(arc) != 12 and smcf.head(arc) != sink ): # Arcs in the solution will have a flow value of 1. # There start and end nodes give an assignment of worker to task. if smcf.flow(arc) > 0: print( "Worker %d assigned to task %d. Cost = %d" % (smcf.tail(arc), smcf.head(arc), smcf.unit_cost(arc)) ) else: print("There was an issue with the min cost flow input.") print(f"Status: {status}")
C++
if (status == MinCostFlow::OPTIMAL) { LOG(INFO) << "Total cost: " << min_cost_flow.OptimalCost(); LOG(INFO) << ""; for (std::size_t i = 0; i < min_cost_flow.NumArcs(); ++i) { // Can ignore arcs leading out of source or intermediate nodes, or into // sink. if (min_cost_flow.Tail(i) != source && min_cost_flow.Tail(i) != 11 && min_cost_flow.Tail(i) != 12 && min_cost_flow.Head(i) != sink) { // Arcs in the solution have a flow value of 1. Their start and end // nodes give an assignment of worker to task. if (min_cost_flow.Flow(i) > 0) { LOG(INFO) << "Worker " << min_cost_flow.Tail(i) << " assigned to task " << min_cost_flow.Head(i) << " Cost: " << min_cost_flow.UnitCost(i); } } } } else { LOG(INFO) << "Solving the min cost flow problem failed."; LOG(INFO) << "Solver status: " << status; }
Java
if (status == MinCostFlow.Status.OPTIMAL) { System.out.println("Total cost: " + minCostFlow.getOptimalCost()); System.out.println(); for (int i = 0; i < minCostFlow.getNumArcs(); ++i) { // Can ignore arcs leading out of source or intermediate nodes, or into sink. if (minCostFlow.getTail(i) != source && minCostFlow.getTail(i) != 11 && minCostFlow.getTail(i) != 12 && minCostFlow.getHead(i) != sink) { // Arcs in the solution have a flow value of 1. Their start and end nodes // give an assignment of worker to task. if (minCostFlow.getFlow(i) > 0) { System.out.println("Worker " + minCostFlow.getTail(i) + " assigned to task " + minCostFlow.getHead(i) + " Cost: " + minCostFlow.getUnitCost(i)); } } } } else { System.out.println("Solving the min cost flow problem failed."); System.out.println("Solver status: " + status); }
C#
if (status == MinCostFlow.Status.OPTIMAL) { Console.WriteLine("Total cost: " + minCostFlow.OptimalCost()); Console.WriteLine(""); for (int i = 0; i < minCostFlow.NumArcs(); ++i) { // Can ignore arcs leading out of source or into sink. if (minCostFlow.Tail(i) != source && minCostFlow.Tail(i) != 11 && minCostFlow.Tail(i) != 12 && minCostFlow.Head(i) != sink) { // Arcs in the solution have a flow value of 1. Their start and end nodes // give an assignment of worker to task. if (minCostFlow.Flow(i) > 0) { Console.WriteLine("Worker " + minCostFlow.Tail(i) + " assigned to task " + minCostFlow.Head(i) + " Cost: " + minCostFlow.UnitCost(i)); } } } } else { Console.WriteLine("Solving the min cost flow problem failed."); Console.WriteLine("Solver status: " + status); }
Aşağıda programın sonucu gösterilmektedir.
Total cost = 250 Worker 1 assigned to task 9. Cost = 75 Worker 2 assigned to task 7. Cost = 35 Worker 5 assigned to task 10. Cost = 75 Worker 6 assigned to task 8. Cost = 65 Time = 0.00031 seconds
A ekibine 9. ve 10. görevler, B ekibine ise 7 ve 8. görevler atanmıştır.
Min. maliyet akış çözücüsünün bu problem için MIP çözücü yaklaşık 0,006 saniye sürer.
Programın tamamı
Programın tamamı aşağıda gösterilmektedir.
Python
"""Assignment with teams of workers.""" from ortools.graph.python import min_cost_flow def main(): """Solving an Assignment with teams of worker.""" smcf = min_cost_flow.SimpleMinCostFlow() # Define the directed graph for the flow. team_a = [1, 3, 5] team_b = [2, 4, 6] start_nodes = ( # fmt: off [0, 0] + [11, 11, 11] + [12, 12, 12] + [1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 5, 6, 6, 6, 6] + [7, 8, 9, 10] # fmt: on ) end_nodes = ( # fmt: off [11, 12] + team_a + team_b + [7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10] + [13, 13, 13, 13] # fmt: on ) capacities = ( # fmt: off [2, 2] + [1, 1, 1] + [1, 1, 1] + [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1] + [1, 1, 1, 1] # fmt: on ) costs = ( # fmt: off [0, 0] + [0, 0, 0] + [0, 0, 0] + [90, 76, 75, 70, 35, 85, 55, 65, 125, 95, 90, 105, 45, 110, 95, 115, 60, 105, 80, 75, 45, 65, 110, 95] + [0, 0, 0, 0] # fmt: on ) source = 0 sink = 13 tasks = 4 # Define an array of supplies at each node. supplies = [tasks, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -tasks] # Add each arc. for i in range(0, len(start_nodes)): smcf.add_arc_with_capacity_and_unit_cost( start_nodes[i], end_nodes[i], capacities[i], costs[i] ) # Add node supplies. for i in range(0, len(supplies)): smcf.set_node_supply(i, supplies[i]) # Find the minimum cost flow between node 0 and node 10. status = smcf.solve() if status == smcf.OPTIMAL: print("Total cost = ", smcf.optimal_cost()) print() for arc in range(smcf.num_arcs()): # Can ignore arcs leading out of source or intermediate, or into sink. if ( smcf.tail(arc) != source and smcf.tail(arc) != 11 and smcf.tail(arc) != 12 and smcf.head(arc) != sink ): # Arcs in the solution will have a flow value of 1. # There start and end nodes give an assignment of worker to task. if smcf.flow(arc) > 0: print( "Worker %d assigned to task %d. Cost = %d" % (smcf.tail(arc), smcf.head(arc), smcf.unit_cost(arc)) ) else: print("There was an issue with the min cost flow input.") print(f"Status: {status}") if __name__ == "__main__": main()
C++
#include <cstdint> #include <vector> #include "ortools/graph/min_cost_flow.h" namespace operations_research { // MinCostFlow simple interface example. void BalanceMinFlow() { // Instantiate a SimpleMinCostFlow solver. SimpleMinCostFlow min_cost_flow; // Define the directed graph for the flow. const std::vector<int64_t> team_A = {1, 3, 5}; const std::vector<int64_t> team_B = {2, 4, 6}; const std::vector<int64_t> start_nodes = { 0, 0, 11, 11, 11, 12, 12, 12, 1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 5, 6, 6, 6, 6, 7, 8, 9, 10}; const std::vector<int64_t> end_nodes = { 11, 12, 1, 3, 5, 2, 4, 6, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 13, 13, 13, 13}; const std::vector<int64_t> capacities = {2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1}; const std::vector<int64_t> unit_costs = { 0, 0, 0, 0, 0, 0, 0, 0, 90, 76, 75, 70, 35, 85, 55, 65, 125, 95, 90, 105, 45, 110, 95, 115, 60, 105, 80, 75, 45, 65, 110, 95, 0, 0, 0, 0}; const int64_t source = 0; const int64_t sink = 13; const int64_t tasks = 4; // Define an array of supplies at each node. const std::vector<int64_t> supplies = {tasks, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -tasks}; // Add each arc. for (int i = 0; i < start_nodes.size(); ++i) { int arc = min_cost_flow.AddArcWithCapacityAndUnitCost( start_nodes[i], end_nodes[i], capacities[i], unit_costs[i]); if (arc != i) LOG(FATAL) << "Internal error"; } // Add node supplies. for (int i = 0; i < supplies.size(); ++i) { min_cost_flow.SetNodeSupply(i, supplies[i]); } // Find the min cost flow. int status = min_cost_flow.Solve(); if (status == MinCostFlow::OPTIMAL) { LOG(INFO) << "Total cost: " << min_cost_flow.OptimalCost(); LOG(INFO) << ""; for (std::size_t i = 0; i < min_cost_flow.NumArcs(); ++i) { // Can ignore arcs leading out of source or intermediate nodes, or into // sink. if (min_cost_flow.Tail(i) != source && min_cost_flow.Tail(i) != 11 && min_cost_flow.Tail(i) != 12 && min_cost_flow.Head(i) != sink) { // Arcs in the solution have a flow value of 1. Their start and end // nodes give an assignment of worker to task. if (min_cost_flow.Flow(i) > 0) { LOG(INFO) << "Worker " << min_cost_flow.Tail(i) << " assigned to task " << min_cost_flow.Head(i) << " Cost: " << min_cost_flow.UnitCost(i); } } } } else { LOG(INFO) << "Solving the min cost flow problem failed."; LOG(INFO) << "Solver status: " << status; } } } // namespace operations_research int main() { operations_research::BalanceMinFlow(); return EXIT_SUCCESS; }
Java
package com.google.ortools.graph.samples; import com.google.ortools.Loader; import com.google.ortools.graph.MinCostFlow; import com.google.ortools.graph.MinCostFlowBase; /** Minimal Assignment Min Flow. */ public class BalanceMinFlow { public static void main(String[] args) throws Exception { Loader.loadNativeLibraries(); // Instantiate a SimpleMinCostFlow solver. MinCostFlow minCostFlow = new MinCostFlow(); // Define the directed graph for the flow. // int[] teamA = new int[] {1, 3, 5}; // int[] teamB = new int[] {2, 4, 6}; int[] startNodes = new int[] {0, 0, 11, 11, 11, 12, 12, 12, 1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 5, 6, 6, 6, 6, 7, 8, 9, 10}; int[] endNodes = new int[] {11, 12, 1, 3, 5, 2, 4, 6, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 13, 13, 13, 13}; int[] capacities = new int[] {2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1}; int[] unitCosts = new int[] {0, 0, 0, 0, 0, 0, 0, 0, 90, 76, 75, 70, 35, 85, 55, 65, 125, 95, 90, 105, 45, 110, 95, 115, 60, 105, 80, 75, 45, 65, 110, 95, 0, 0, 0, 0}; int source = 0; int sink = 13; int tasks = 4; // Define an array of supplies at each node. int[] supplies = new int[] {tasks, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -tasks}; // Add each arc. for (int i = 0; i < startNodes.length; ++i) { int arc = minCostFlow.addArcWithCapacityAndUnitCost( startNodes[i], endNodes[i], capacities[i], unitCosts[i]); if (arc != i) { throw new Exception("Internal error"); } } // Add node supplies. for (int i = 0; i < supplies.length; ++i) { minCostFlow.setNodeSupply(i, supplies[i]); } // Find the min cost flow. MinCostFlowBase.Status status = minCostFlow.solve(); if (status == MinCostFlow.Status.OPTIMAL) { System.out.println("Total cost: " + minCostFlow.getOptimalCost()); System.out.println(); for (int i = 0; i < minCostFlow.getNumArcs(); ++i) { // Can ignore arcs leading out of source or intermediate nodes, or into sink. if (minCostFlow.getTail(i) != source && minCostFlow.getTail(i) != 11 && minCostFlow.getTail(i) != 12 && minCostFlow.getHead(i) != sink) { // Arcs in the solution have a flow value of 1. Their start and end nodes // give an assignment of worker to task. if (minCostFlow.getFlow(i) > 0) { System.out.println("Worker " + minCostFlow.getTail(i) + " assigned to task " + minCostFlow.getHead(i) + " Cost: " + minCostFlow.getUnitCost(i)); } } } } else { System.out.println("Solving the min cost flow problem failed."); System.out.println("Solver status: " + status); } } private BalanceMinFlow() {} }
C#
using System; using Google.OrTools.Graph; public class BalanceMinFlow { static void Main() { // Instantiate a SimpleMinCostFlow solver. MinCostFlow minCostFlow = new MinCostFlow(); // Define the directed graph for the flow. int[] teamA = { 1, 3, 5 }; int[] teamB = { 2, 4, 6 }; // Define four parallel arrays: sources, destinations, capacities, and unit costs // between each pair. int[] startNodes = { 0, 0, 11, 11, 11, 12, 12, 12, 1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 5, 6, 6, 6, 6, 7, 8, 9, 10 }; int[] endNodes = { 11, 12, 1, 3, 5, 2, 4, 6, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 7, 8, 9, 10, 13, 13, 13, 13 }; int[] capacities = { 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 }; int[] unitCosts = { 0, 0, 0, 0, 0, 0, 0, 0, 90, 76, 75, 70, 35, 85, 55, 65, 125, 95, 90, 105, 45, 110, 95, 115, 60, 105, 80, 75, 45, 65, 110, 95, 0, 0, 0, 0 }; int source = 0; int sink = 13; int tasks = 4; // Define an array of supplies at each node. int[] supplies = { tasks, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, -tasks }; // Add each arc. for (int i = 0; i < startNodes.Length; ++i) { int arc = minCostFlow.AddArcWithCapacityAndUnitCost(startNodes[i], endNodes[i], capacities[i], unitCosts[i]); if (arc != i) throw new Exception("Internal error"); } // Add node supplies. for (int i = 0; i < supplies.Length; ++i) { minCostFlow.SetNodeSupply(i, supplies[i]); } // Find the min cost flow. MinCostFlow.Status status = minCostFlow.Solve(); if (status == MinCostFlow.Status.OPTIMAL) { Console.WriteLine("Total cost: " + minCostFlow.OptimalCost()); Console.WriteLine(""); for (int i = 0; i < minCostFlow.NumArcs(); ++i) { // Can ignore arcs leading out of source or into sink. if (minCostFlow.Tail(i) != source && minCostFlow.Tail(i) != 11 && minCostFlow.Tail(i) != 12 && minCostFlow.Head(i) != sink) { // Arcs in the solution have a flow value of 1. Their start and end nodes // give an assignment of worker to task. if (minCostFlow.Flow(i) > 0) { Console.WriteLine("Worker " + minCostFlow.Tail(i) + " assigned to task " + minCostFlow.Head(i) + " Cost: " + minCostFlow.UnitCost(i)); } } } } else { Console.WriteLine("Solving the min cost flow problem failed."); Console.WriteLine("Solver status: " + status); } } }