The solution of a linear program. 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 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
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('Objective value: ' + solution.getObjectiveValue());
Logger.log('Value of x: ' + solution.getVariableValue('x'));
Logger.log('Value of y: ' + solution.getVariableValue('y'));
}
Methods
Method | Return type | Brief description |
---|---|---|
getObjectiveValue() | Number | Gets the value of the objective function in the current solution. |
getStatus() | Status | Gets the status of the solution. |
getVariableValue(variableName) | Number | Gets the value of a variable in the solution created by the last call to
LinearOptimizationEngine.solve() . |
isValid() | Boolean | Determines whether the solution is either feasible or optimal. |
Detailed documentation
getObjectiveValue()
Gets the value of the objective function in the current solution.
var engine = LinearOptimizationService.createEngine();
// Add variables, constraints and define the objective with addVariable(), addConstraint(), etc
engine.addVariable('x', 0, 10);
// ...
// Solve the linear program
var solution = engine.solve();
Logger.log('ObjectiveValue: ' + solution.getObjectiveValue());
Return
Number
— the value of the objective function
getStatus()
Gets the status of the solution. Before solving a problem, the status will be
NOT_SOLVED
.
var engine = LinearOptimizationService.createEngine();
// Add variables, constraints and define the objective with addVariable(), addConstraint(), etc
engine.addVariable('x', 0, 10);
// ...
// Solve the linear program
var solution = engine.solve();
if (solution.getStatus() != LinearOptimizationService.Status.FEASIBLE &&
solution.getStatus() != LinearOptimizationService.Status.OPTIMAL) {
throw 'No solution ' + status;
}
Logger.log('Status: ' + solution.getStatus());
Return
Status
— the status of the solver
getVariableValue(variableName)
Gets the value of a variable in the solution created by the last call to
LinearOptimizationEngine.solve()
.
var engine = LinearOptimizationService.createEngine();
// Add variables, constraints and define the objective with addVariable(), addConstraint(), etc
engine.addVariable('x', 0, 10);
// ...
// Solve the linear program
var solution = engine.solve();
Logger.log('Value of x: ' + solution.getVariableValue('x'));
Parameters
Name | Type | Description |
---|---|---|
variableName | String | name of the variable |
Return
Number
— the value of the variable in the solution
isValid()
Determines whether the solution is either feasible or optimal.
var engine = LinearOptimizationService.createEngine();
// Add variables, constraints and define the objective with addVariable(), addConstraint(), etc
engine.addVariable('x', 0, 10);
// ...
// Solve the linear program
var solution = engine.solve();
if (!solution.isValid()) {
throw 'No solution ' + status;
}
Return
Boolean
— true
if the solution is valid (Status.FEASIBLE
or
Status.OPTIMAL
); false
if not