Class LinearOptimizationSolution

LinearOptimizationSolution

線性規劃的解。以下範例會解決下列線性程式：

兩個變數，x 和 y：
0 ≤ x ≤ 10
0 ≤ y ≤ 5

限制：
0 ≤ 2 * x + 5 * y ≤ 10
0 ≤ 10 * x + 3 * y ≤ 20

目標：
盡量爭取x + y 

const 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
let constraint = engine.addConstraint(0, 10);
constraint.setCoefficient('x', 2);
constraint.setCoefficient('y', 5);

// Create the constraint: 0 <= 10 * x + 3 * y <= 20
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
const 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')}`);
}

方法

方法傳回類型簡短說明
getObjectiveValue()Number取得目前解決方案中目標函式的值。
getStatus()Status取得解決方案的狀態。
getVariableValue(variableName)Number取得上次呼叫 LinearOptimizationEngine.solve() 所建立解決方案中的變數值。
isValid()Boolean判斷解決方案是否可行或最佳。

內容詳盡的說明文件

getObjectiveValue()

取得目前解決方案中目標函式的值。

const engine = LinearOptimizationService.createEngine();

// Add variables, constraints and define the objective with addVariable(),
// addConstraint(), etc
engine.addVariable('x', 0, 10);

// ...

// Solve the linear program
const solution = engine.solve();
Logger.log(`ObjectiveValue: ${solution.getObjectiveValue()}`);

回攻員

Number：目標函式的值

getStatus()

取得解決方案的狀態。解決問題前，狀態會顯示為「NOT_SOLVED」。 

const engine = LinearOptimizationService.createEngine();

// Add variables, constraints and define the objective with addVariable(),
// addConstraint(), etc
engine.addVariable('x', 0, 10);

// ...

// Solve the linear program
const solution = engine.solve();
const status = solution.getStatus();

if (status !== LinearOptimizationService.Status.FEASIBLE &&
    status !== LinearOptimizationService.Status.OPTIMAL) {
  throw `No solution ${status}`;
}
Logger.log(`Status: ${status}`);

回攻員

Status：求解器的狀態

getVariableValue(variableName)

取得上次呼叫 LinearOptimizationEngine.solve() 所建立解決方案中的變數值。 

const engine = LinearOptimizationService.createEngine();

// Add variables, constraints and define the objective with addVariable(),
// addConstraint(), etc
engine.addVariable('x', 0, 10);

// ...

// Solve the linear program
const solution = engine.solve();
Logger.log(`Value of x: ${solution.getVariableValue('x')}`);

參數

名稱類型說明
variableNameString變數名稱

回攻員

Number：解決方案中的變數值

isValid()

判斷解決方案是否可行或最佳。 

const engine = LinearOptimizationService.createEngine();

// Add variables, constraints and define the objective with addVariable(),
// addConstraint(), etc
engine.addVariable('x', 0, 10);

// ...

// Solve the linear program
const solution = engine.solve();
if (!solution.isValid()) {
  throw `No solution ${solution.getStatus()}`;
}

回攻員

Boolean：解決方案有效 (Status.FEASIBLE 或 Status.OPTIMAL)；true：解決方案無效；false：解決方案未知