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LinearOptimizationService
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
constengine=LinearOptimizationService.createEngine();// Add variables, constraints and define the objective using addVariable(),// addConstraint(), etc. Add two variables, 0 <= x <= 10 and 0 <= y <= 5engine.addVariable('x',0,10);engine.addVariable('y',0,5);// Create the constraint: 0 <= 2 * x + 5 * y <= 10letconstraint=engine.addConstraint(0,10);constraint.setCoefficient('x',2);constraint.setCoefficient('y',5);// Create the constraint: 0 <= 10 * x + 3 * y <= 20constraint=engine.addConstraint(0,20);constraint.setCoefficient('x',10);constraint.setCoefficient('y',3);// Set the objective to be x + yengine.setObjectiveCoefficient('x',1);engine.setObjectiveCoefficient('y',1);// Engine should maximize the objective.engine.setMaximization();// Solve the linear programconstsolution=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')}`);}
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-12-02 UTC."],[[["\u003cp\u003eThe Linear Optimization Service enables the modeling and resolution of linear and mixed-integer linear programs within Apps Script.\u003c/p\u003e\n"],["\u003cp\u003eIt provides functionalities to define variables, constraints, and objectives for optimization problems.\u003c/p\u003e\n"],["\u003cp\u003eThe service utilizes a dedicated engine, created via \u003ccode\u003ecreateEngine()\u003c/code\u003e, to process and solve the defined linear programs.\u003c/p\u003e\n"],["\u003cp\u003eSolutions can be retrieved and assessed for validity, providing values for optimized variables or indicating an infeasible solution.\u003c/p\u003e\n"],["\u003cp\u003eDevelopers can access detailed documentation and examples for utilizing the Linear Optimization Service effectively.\u003c/p\u003e\n"]]],["The `LinearOptimizationService` solves linear and mixed-integer linear programs. Key actions include creating an engine via `createEngine()`, adding variables (e.g., 'x', 'y') with bounds using `addVariable()`, and defining constraints with `addConstraint()` and `setCoefficient()`. The objective is set using `setObjectiveCoefficient()`, specifying maximization with `setMaximization()`. Finally, `solve()` computes the solution, and results are accessed via methods such as `getVariableValue()`. The service also includes properties like `Status` and `VariableType`.\n"],null,["# Class LinearOptimizationService\n\nLinearOptimizationService\n\nThe linear optimization service, used to model and solve linear and mixed-integer linear\nprograms. The example below solves the following linear program:\n\nTwo variables, `x` and `y`: \n\n\n`0 ≤ x ≤ 10`\n\n\n`0 ≤ y ≤ 5`\n\n\nConstraints: \n\n\n`0 ≤ 2 * x + 5 * y ≤ 10`\n\n\n`0 ≤ 10 * x + 3 * y ≤ 20`\n\n\nObjective: \n\nMaximize `x + y`\n\n\n```javascript\nconst engine = LinearOptimizationService.createEngine();\n\n// Add variables, constraints and define the objective using addVariable(),\n// addConstraint(), etc. Add two variables, 0 \u003c= x \u003c= 10 and 0 \u003c= y \u003c= 5\nengine.addVariable('x', 0, 10);\nengine.addVariable('y', 0, 5);\n\n// Create the constraint: 0 \u003c= 2 * x + 5 * y \u003c= 10\nlet constraint = engine.addConstraint(0, 10);\nconstraint.setCoefficient('x', 2);\nconstraint.setCoefficient('y', 5);\n\n// Create the constraint: 0 \u003c= 10 * x + 3 * y \u003c= 20\nconstraint = engine.addConstraint(0, 20);\nconstraint.setCoefficient('x', 10);\nconstraint.setCoefficient('y', 3);\n\n// Set the objective to be x + y\nengine.setObjectiveCoefficient('x', 1);\nengine.setObjectiveCoefficient('y', 1);\n\n// Engine should maximize the objective.\nengine.setMaximization();\n\n// Solve the linear program\nconst solution = engine.solve();\nif (!solution.isValid()) {\n Logger.log(`No solution ${solution.getStatus()}`);\n} else {\n Logger.log(`Value of x: ${solution.getVariableValue('x')}`);\n Logger.log(`Value of y: ${solution.getVariableValue('y')}`);\n}\n``` \n\n### Properties\n\n| Property | Type | Description |\n|------------------|-------------------------------------------------------------------|------------------------------------------|\n| `Status` | [Status](/apps-script/reference/optimization/status) | Status of the solver. |\n| `Variable``Type` | [VariableType](/apps-script/reference/optimization/variable-type) | Type of variables created by the solver. |\n\n### Methods\n\n| Method | Return type | Brief description |\n|-----------------------------------|--------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------|\n| [createEngine()](#createEngine()) | [LinearOptimizationEngine](/apps-script/reference/optimization/linear-optimization-engine) | Creates an engine to to solve linear programs (potentially mixed-integer programs). |\n\nDetailed documentation\n----------------------\n\n### `create``Engine()`\n\nCreates an engine to to solve linear programs (potentially mixed-integer programs).\n\n```javascript\n// Creates a linear optimization engine.\nconst engine = LinearOptimizationService.createEngine();\nengine.addVariable('x', 0, 10);\n\n// ...\n```\n\n#### Return\n\n\n[LinearOptimizationEngine](/apps-script/reference/optimization/linear-optimization-engine) --- a linear optimization engine"]]
