Mesin yang digunakan untuk membuat model dan memecahkan program linear. Contoh di bawah ini menyelesaikan program linear berikut:
Dua variabel, x
dan y
:
0 ≤ x ≤ 10
0 ≤ y ≤ 5
Batasan:
0 ≤ 2 * x + 5 * y ≤ 10
0 ≤ 10 * x + 3 * y ≤ 20
Tujuan:
Maksimalkan x + y
const engine = LinearOptimizationService.createEngine(); // Add variables, constraints and define the objective with addVariable(), // addConstraint(), etc Add two variables, 0 <= x <= 10 and 0 <= y <= 5 engine.addVariable('x', 0, 10); engine.addVariable('y', 0, 5); // Create the constraint: 0 <= 2 * x + 5 * y <= 10 let constraint = engine.addConstraint(0, 10); constraint.setCoefficient('x', 2); constraint.setCoefficient('y', 5); // Create the constraint: 0 <= 10 * x + 3 * y <= 20 constraint = engine.addConstraint(0, 20); constraint.setCoefficient('x', 10); constraint.setCoefficient('y', 3); // Set the objective to be x + y engine.setObjectiveCoefficient('x', 1); engine.setObjectiveCoefficient('y', 1); // Engine should maximize the objective engine.setMaximization(); // Solve the linear program const solution = engine.solve(); if (!solution.isValid()) { Logger.log(`No solution ${solution.getStatus()}`); } else { Logger.log(`Value of x: ${solution.getVariableValue('x')}`); Logger.log(`Value of y: ${solution.getVariableValue('y')}`); }
Metode
Dokumentasi mendetail
add Constraint(lowerBound, upperBound)
Menambahkan batasan linear baru dalam model. Batas atas dan bawah batasan ditentukan
pada waktu pembuatan. Koefisien untuk variabel ditentukan melalui panggilan ke Linear
.
const engine = LinearOptimizationService.createEngine(); // Create a linear constraint with the bounds 0 and 10 const constraint = engine.addConstraint(0, 10); // Create a variable so we can add it to the constraint engine.addVariable('x', 0, 5); // Set the coefficient of the variable in the constraint. The constraint is now: // 0 <= 2 * x <= 5 constraint.setCoefficient('x', 2);
Parameter
Nama | Jenis | Deskripsi |
---|---|---|
lower | Number | batas bawah batasan |
upper | Number | batas atas batasan |
Pulang pergi
Linear
— batasan yang dibuat
add Constraints(lowerBounds, upperBounds, variableNames, coefficients)
Menambahkan batasan dalam batch ke model.
const engine = LinearOptimizationService.createEngine(); // Add a boolean variable 'x' (integer >= 0 and <= 1) and a real (continuous >= // 0 and <= 100) variable 'y'. engine.addVariables( ['x', 'y'], [0, 0], [1, 100], [ LinearOptimizationService.VariableType.INTEGER, LinearOptimizationService.VariableType.CONTINUOUS, ], ); // Adds two constraints: // 0 <= x + y <= 3 // 1 <= 10 * x - y <= 5 engine.addConstraints( [0.0, 1.0], [3.0, 5.0], [ ['x', 'y'], ['x', 'y'], ], [ [1, 1], [10, -1], ], );
Parameter
Nama | Jenis | Deskripsi |
---|---|---|
lower | Number[] | batas bawah batasan |
upper | Number[] | batas atas batasan |
variable | String[][] | nama variabel yang koefisiennya ditetapkan |
coefficients | Number[][] | koefisien yang ditetapkan |
Pulang pergi
Linear
— mesin pengoptimalan linear
add Variable(name, lowerBound, upperBound)
Menambahkan variabel kontinu baru ke model. Variabel direferensikan dengan namanya. Jenisnya
ditetapkan ke Variable
.
const engine = LinearOptimizationService.createEngine(); const constraint = engine.addConstraint(0, 10); // Add a boolean variable (integer >= 0 and <= 1) engine.addVariable('x', 0, 1, LinearOptimizationService.VariableType.INTEGER); // Add a real (continuous) variable. Notice the lack of type specification. engine.addVariable('y', 0, 100);
Parameter
Nama | Jenis | Deskripsi |
---|---|---|
name | String | nama unik variabel |
lower | Number | batas bawah variabel |
upper | Number | batas atas variabel |
Pulang pergi
Linear
— mesin pengoptimalan linear
add Variable(name, lowerBound, upperBound, type)
Menambahkan variabel baru ke model. Variabel direferensikan dengan namanya.
const engine = LinearOptimizationService.createEngine(); const constraint = engine.addConstraint(0, 10); // Add a boolean variable (integer >= 0 and <= 1) engine.addVariable('x', 0, 1, LinearOptimizationService.VariableType.INTEGER); // Add a real (continuous) variable engine.addVariable( 'y', 0, 100, LinearOptimizationService.VariableType.CONTINUOUS, );
Parameter
Nama | Jenis | Deskripsi |
---|---|---|
name | String | nama unik variabel |
lower | Number | batas bawah variabel |
upper | Number | batas atas variabel |
type | Variable | jenis variabel, dapat berupa salah satu dari Variable |
Pulang pergi
Linear
— mesin pengoptimalan linear
add Variable(name, lowerBound, upperBound, type, objectiveCoefficient)
Menambahkan variabel baru ke model. Variabel direferensikan dengan namanya.
const engine = LinearOptimizationService.createEngine(); const constraint = engine.addConstraint(0, 10); // Add a boolean variable (integer >= 0 and <= 1) engine.addVariable( 'x', 0, 1, LinearOptimizationService.VariableType.INTEGER, 2, ); // The objective is now 2 * x. // Add a real (continuous) variable engine.addVariable( 'y', 0, 100, LinearOptimizationService.VariableType.CONTINUOUS, -5, ); // The objective is now 2 * x - 5 * y.
Parameter
Nama | Jenis | Deskripsi |
---|---|---|
name | String | nama unik variabel |
lower | Number | batas bawah variabel |
upper | Number | batas atas variabel |
type | Variable | jenis variabel, dapat berupa salah satu dari Variable |
objective | Number | koefisien objektif variabel |
Pulang pergi
Linear
— mesin pengoptimalan linear
add Variables(names, lowerBounds, upperBounds, types, objectiveCoefficients)
Menambahkan variabel dalam batch ke model. Variabel dirujuk berdasarkan namanya.
const engine = LinearOptimizationService.createEngine(); // Add a boolean variable 'x' (integer >= 0 and <= 1) and a real (continuous >=0 // and <= 100) variable 'y'. engine.addVariables( ['x', 'y'], [0, 0], [1, 100], [ LinearOptimizationService.VariableType.INTEGER, LinearOptimizationService.VariableType.CONTINUOUS, ], );
Parameter
Nama | Jenis | Deskripsi |
---|---|---|
names | String[] | nama unik variabel |
lower | Number[] | batas bawah variabel |
upper | Number[] | batas atas variabel |
types | Variable | jenis variabel, dapat berupa salah satu dari Variable |
objective | Number[] | koefisien objektif variabel |
Pulang pergi
Linear
— mesin pengoptimalan linear
set Maximization()
Menetapkan arah pengoptimalan untuk memaksimalkan fungsi tujuan linear.
const engine = LinearOptimizationService.createEngine(); // Add a real (continuous) variable. Notice the lack of type specification. engine.addVariable('y', 0, 100); // Set the coefficient of 'y' in the objective. // The objective is now 5 * y engine.setObjectiveCoefficient('y', 5); // We want to maximize. engine.setMaximization();
Pulang pergi
Linear
— mesin pengoptimalan linear
set Minimization()
Menetapkan arah pengoptimalan untuk meminimalkan fungsi tujuan linear.
const engine = LinearOptimizationService.createEngine(); // Add a real (continuous) variable. Notice the lack of type specification. engine.addVariable('y', 0, 100); // Set the coefficient of 'y' in the objective. // The objective is now 5 * y engine.setObjectiveCoefficient('y', 5); // We want to minimize engine.setMinimization();
Pulang pergi
Linear
— mesin pengoptimalan linear
set Objective Coefficient(variableName, coefficient)
Menetapkan koefisien variabel dalam fungsi tujuan linear.
const engine = LinearOptimizationService.createEngine(); // Add a real (continuous) variable. Notice the lack of type specification. engine.addVariable('y', 0, 100); // Set the coefficient of 'y' in the objective. // The objective is now 5 * y engine.setObjectiveCoefficient('y', 5);
Parameter
Nama | Jenis | Deskripsi |
---|---|---|
variable | String | nama variabel yang koefisiennya ditetapkan |
coefficient | Number | koefisien variabel dalam fungsi tujuan |
Pulang pergi
Linear
— mesin pengoptimalan linear
solve()
Menyelesaikan program linear saat ini dengan batas waktu default 30 detik. Menampilkan solusi yang ditemukan.
const engine = LinearOptimizationService.createEngine(); // Add variables, constraints and define the objective with addVariable(), // addConstraint(), etc engine.addVariable('x', 0, 10); // ... // Solve the linear program const solution = engine.solve(); if (!solution.isValid()) { throw `No solution ${solution.getStatus()}`; } Logger.log(`Value of x: ${solution.getVariableValue('x')}`);
Pulang pergi
Linear
— solusi pengoptimalan
solve(seconds)
Menyelesaikan program linear saat ini. Menampilkan solusi yang ditemukan. dan apakah solusi tersebut optimal.
const engine = LinearOptimizationService.createEngine(); // Add variables, constraints and define the objective with addVariable(), // addConstraint(), etc engine.addVariable('x', 0, 10); // ... // Solve the linear program const solution = engine.solve(300); if (!solution.isValid()) { throw `No solution ${solution.getStatus()}`; } Logger.log(`Value of x: ${solution.getVariableValue('x')}`);
Parameter
Nama | Jenis | Deskripsi |
---|---|---|
seconds | Number | batas waktu untuk menyelesaikan masalah, dalam detik; batas waktu maksimum adalah 300 detik |
Pulang pergi
Linear
— solusi pengoptimalan