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Служба линейной оптимизации
Служба линейной оптимизации, используемая для моделирования и решения линейных и смешанно-целочисленных линейных программ. В приведенном ниже примере решается следующая линейная программа:
Две переменные, x и y : 0 ≤ x ≤ 10 0 ≤ y ≤ 5
Ограничения: 0 ≤ 2 * x + 5 * y ≤ 10 0 ≤ 10 * x + 3 * y ≤ 20
Цель: Максимизировать 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')}`);}
[[["Прост для понимания","easyToUnderstand","thumb-up"],["Помог мне решить мою проблему","solvedMyProblem","thumb-up"],["Другое","otherUp","thumb-up"]],[["Отсутствует нужная мне информация","missingTheInformationINeed","thumb-down"],["Слишком сложен/слишком много шагов","tooComplicatedTooManySteps","thumb-down"],["Устарел","outOfDate","thumb-down"],["Проблема с переводом текста","translationIssue","thumb-down"],["Проблемы образцов/кода","samplesCodeIssue","thumb-down"],["Другое","otherDown","thumb-down"]],["Последнее обновление: 2025-07-24 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,[]]