Overview
PuLP is a Python library that facilitates the creation and solution of linear and mixed-integer programming (MILP) problems. It acts as a modeler, enabling users to define optimization problems in a Pythonic way and then solve them using various open-source or commercial solvers. PuLP can generate MPS or LP files, allowing for solver interoperability. It supports solvers like GLPK, COIN-OR CLP/CBC (included by default), CPLEX, GUROBI, MOSEK, XPRESS, CHOCO, MIPCL, HiGHS, and SCIP/FSCIP. The library offers essential classes, like LpProblem for defining problems, LpVariable for defining variables with constraints, and LpConstraint for setting limitations. With functions like value() to get variable values and lpSum() or lpDot() for creating linear expressions, PuLP allows efficient model formulation, making it useful for resource allocation, scheduling, supply chain optimization, and other decision-making problems.