Object storing a linear constraint of the form lowerBound ≤ Sum(a(i) x(i)) ≤ upperBound
where lowerBound and upperBound are constants, a(i) are constant
coefficients and x(i) are variables (unknowns).
[[["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complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-12-02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 classes like \u003ccode\u003eLinearOptimizationConstraint\u003c/code\u003e, \u003ccode\u003eLinearOptimizationEngine\u003c/code\u003e, and \u003ccode\u003eLinearOptimizationSolution\u003c/code\u003e to define, solve, and retrieve optimization results.\u003c/p\u003e\n"],["\u003cp\u003e\u003ccode\u003eLinearOptimizationEngine\u003c/code\u003e allows adding variables, constraints, setting objective functions (maximization or minimization), and solving the linear program.\u003c/p\u003e\n"],["\u003cp\u003eSolutions can be evaluated using methods like \u003ccode\u003egetObjectiveValue\u003c/code\u003e, \u003ccode\u003egetStatus\u003c/code\u003e, and \u003ccode\u003egetVariableValue\u003c/code\u003e to understand the optimization outcome.\u003c/p\u003e\n"],["\u003cp\u003eThe service utilizes various statuses (e.g., \u003ccode\u003eOPTIMAL\u003c/code\u003e, \u003ccode\u003eFEASIBLE\u003c/code\u003e, \u003ccode\u003eINFEASIBLE\u003c/code\u003e) and variable types (\u003ccode\u003eINTEGER\u003c/code\u003e, \u003ccode\u003eCONTINUOUS\u003c/code\u003e) to represent the solution state and variable characteristics.\u003c/p\u003e\n"]]],["The linear optimization service models and solves linear and mixed-integer linear programs. Key actions include: creating an engine (`LinearOptimizationEngine`), adding variables with bounds and types, adding constraints to the model, setting the objective function's direction (maximize or minimize), and setting coefficients for variables in the objective function and constraints. The `solve()` method then computes the solution. The `LinearOptimizationSolution` object contains methods to determine solution status, objective value, and variable values.\n"],null,[]]
