The linear optimization service, used to model and solve linear and mixed-integer linear programs. The example below solves the following linear program:
Two variables, x and y:
0 ≤ x ≤ 10
0 ≤ y ≤ 5
Constraints:
0 ≤ 2 * x + 5 * y ≤ 10
0 ≤ 10 * x + 3 * y ≤ 20
Objective:
Maximize x + y
var engine = LinearOptimizationService.createEngine();
// Add variables, constraints and define the objective using 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
var constraint = engine.addConstraint(0, 10);
constraint.setCoefficient('x', 2);
constraint.setCoefficient('y', 5);
// Create the constraint: 0 <= 10 * x + 3 * y <= 20
var 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
var 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'));
}
Properties
| Property | Type | Description |
|---|---|---|
Status | Status | Status of the solver. |
VariableType | VariableType | Type of variables created by the solver. |
Methods
| Method | Return type | Brief description |
|---|---|---|
createEngine() | LinearOptimizationEngine | Creates an engine to to solve linear programs (potentially mixed-integer programs). |
Detailed documentation
createEngine()
Creates an engine to to solve linear programs (potentially mixed-integer programs).
// Creates a linear optimization engine.
var engine = LinearOptimizationService.createEngine();
engine.addVariable('x', 0, 10);
// ...
Return
LinearOptimizationEngine — a linear optimization engine