Linear Programming Search

PulpSearch

Solver name is “Pulp”.

class flopt.solvers.pulp_search.PulpSearch

API for PuLP, linear programming modeling tool

Parameters

solver (pulp.Solver) – solver pulp use, see https://coin-or.github.io/pulp/technical/solvers.html. default is pulp.PULP_CBC_CMD

Examples

import flopt

# Variables
a = flopt.Variable("a", lowBound=0, upBound=1, cat="Integer")
b = flopt.Variable("b", lowBound=1, upBound=2, cat="Continuous")
c = flopt.Variable("c", lowBound=-1, upBound=3, cat="Continuous")

# Problem
prob = flopt.Problem()
prob += a + b + c + 2
prob += a + b >= 2
prob += b - c >= 3

prob.solve(solver="Pulp", msg=True)

When you use other solvers in pulp, for example GLPK solver, you set solver parameter in PulpSearch object.

solver = flopt.Solver("Pulp")

import pulp
glpk_solver = pulp.GLPK_CMD()
solver.setParams(solver=glpk_solver)
prob.solve(solver, msg=True)

ScipyMilpSearch

Solver name is “ScipyMilp”.

class flopt.solvers.scipy_searches.ScipyMilpSearch

Scipy optimize milp API Solver

Note

In scipy version 1.9.0, we can not obtain the incumbent solution from scipy.optimize.milp API, and can not use callback to this API for logging. Therefore, we can obtain the solution when only scipy.optimize.milp terminate the execution normally.

Examples

import flopt

# Variables
a = flopt.Variable("a", lowBound=0, upBound=1, cat="Integer")
b = flopt.Variable("b", lowBound=1, upBound=2, cat="Continuous")
c = flopt.Variable("c", lowBound=-1, upBound=3, cat="Continuous")

# Problem
prob = flopt.Problem()
prob += a + b + c + 2
prob += a + b >= 2
prob += b - c >= 3

solver = flopt.Solver("ScipyMilp")
prob.solve(solver, msg=True)

See also

scipy.optimize.milp