A Python library for modeling and solving linear programming (LP) and mixed-integer linear programming (MILP) optimization problems.
PuLP
- Python
- Automation, Data Analytics, Mathematics, PLM & ERP, Process Control
- Predictive Maintenance Algorithms, Process Optimization, Resource-Efficient Products, Statistical Analysis, Sustainability Metrics
Features:
- LP/MILP problem modeling,Pythonic syntax for variables,constraints,objectives,interfaces with various solvers (CBC,Gurobi,CPLEX,GLPK,SCIP),problem export to MPS/LP formats,sensitivity analysis (solver dependent),status checking of solutions
Pricing:
- Free
- Easy to use for defining LP/MILP problems in Python, solver-agnostic (can switch solvers easily), open-source, good documentation and examples, part of the COIN-OR suite.
- Limited to LP/MILP problems (no nonlinear support directly without extensions), performance depends heavily on the chosen underlying solver, error messages from solvers can be cryptic.
Best for:
- Operations researchers, data scientists, and engineers who need to model and solve linear or mixed-integer optimization problems for planning, scheduling, and resource allocation.