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@revolugo/ortools
Advanced tools
Readme
A node.js wrapper for Google OR-Tools.
Current implementation only wraps integer programming necessary classes and methods. It exposes a Promise interface for the solver.solve()
method.
The following OR-Tools C++ Library values, classes and methods are supported.
note : corresponding javascript class methods are camelCase-d (e.g. makeIntVar()
)
Supported optimization problem type:
MPSolver::CBC_MIXED_INTEGER_PROGRAMMING
Methods:
MPSolver::Name()
MPSolver::NumVariables()
MPSolver::NumConstraints()
MPSolver::MakeIntVar()
MPSolver::MakeRowConstraint()
MPSolver::MakeMutableObjective()
MPSolver::Solve()
MPSolver::infinity()
MPSolver::wall_time()
MPSolver::iterations()
MPSolver::nodes()
Methods:
MPVariable::Name()
MPVariable::solution_value()
Methods:
MPConstraint::SetCoefficient()
Methods:
MPObjective::SetCoefficient()
MPObjective::SetMaximization()
MPObjective::SetMinimization()
MPObjective::Value()
npm install @revolugo/ortools --save
note: the package includes a script that detects your platform (OS/version) and downloads the right binaries and include files from Google OR-Tools repository releases. Building the module requires standard C/C++ build tools and zlib. Supported platforms are currently:
const ortools = require('@revolugo/ortools')
// Create the linear solver with the CBC backend.
const solver = new ortools.MPSolver('My solver', ortools.MPSolver.CBC_MIXED_INTEGER_PROGRAMMING)
// Create the variables x and y.
const x = solver.makeIntVar(0, solver.infinity(), 'x')
const y = solver.makeIntVar(0, solver.infinity(), 'y')
// Create a linear constraint, x + 7y <= 17.5.
const c0 = solver.makeRowConstraint(-solver.infinity(), 17.5)
c0.setCoefficient(x, 1)
c0.setCoefficient(y, 7)
// Create another linear constraint, x <= 3.5.
const c1 = solver.makeRowConstraint(-solver.infinity(), 3.5)
c1.setCoefficient(x, 1)
c1.setCoefficient(y, 0)
// Create the objective function, x + 10y.
const objective = solver.mutableObjective()
objective.setCoefficient(x, 1)
objective.setCoefficient(y, 10)
// We want the objective to be at a maximum value
objective.setMaximization()
// Try to find the best solution using solve()
// Returns mapped MPSolver::ResultStatus enum value
// ortools.MPSolver.RESULT_OPTIMAL
// ortools.MPSolver.RESULT_FEASIBLE
// ortools.MPSolver.RESULT_INFEASIBLE
// ortools.MPSolver.RESULT_UNBOUNDED
// ortools.MPSolver.RESULT_ABNORMAL
// ortools.MPSolver.RESULT_NOT_SOLVED
// ortools.MPSolver.RESULT_MODEL_INVALID
;(async () => {
const result = await solver.solve()
if (result === ortools.MPSolver.RESULT_OPTIMAL) {
console.log('Solution:')
console.log(`x = ${ x.solution_value() }`)
console.log(`y = ${ y.solution_value() }`)
console.log(`objective = ${ objective.value() }`)
}
else {
console.log(`Non optimal result ${ result }!`)
}
})();
FAQs
Nodejs bindings for or-tools
The npm package @revolugo/ortools receives a total of 5 weekly downloads. As such, @revolugo/ortools popularity was classified as not popular.
We found that @revolugo/ortools demonstrated a not healthy version release cadence and project activity because the last version was released a year ago. It has 2 open source maintainers collaborating on the project.
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