Class LinearOptimizationSolution

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