A Python library for modeling and solving linear programming (LP) and mixed-integer linear programming (MILP) optimization problems.
PuLP

- Python
- Automatización, Análisis de datos, Matemáticas, PLM y ERP, Control de procesos
- Algoritmos de mantenimiento predictivo, Optimización de procesos, Productos eficientes en el uso de los recursos, Análisis estadístico, Métricas de sostenibilidad
Características:
- 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
Precios:
- Gratis
- 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.
Ideal para:
- Operations researchers, data scientists, and engineers who need to model and solve linear or mixed-integer optimization problems for planning, scheduling, and resource allocation.