GNU Linear Programming Kit vs lpsolve

Struggling to choose between GNU Linear Programming Kit and lpsolve? Both products offer unique advantages, making it a tough decision.

GNU Linear Programming Kit is a Development solution with tags like linear-programming, optimization, solver.

It boasts features such as Linear programming solver, Mixed integer programming solver, Network flow/graph optimization capabilities, Support for writing models in GNU MathProg modeling language, APIs for C, C++, Java, Python, OCaml, PHP, Ruby, R, Command line tools glpsol for solving models, Modeling language translator glpsol and pros including Free and open source, High performance solver, Support for large scale problems, APIs for many programming languages, Active development community.

On the other hand, lpsolve is a Development product tagged with linear-programming, solver, optimization, modeling-language.

Its standout features include Formulate linear programming models, Solve models with revised simplex method, Solve models with primal-dual interior point method, Handle integer variables, Import/export models in MPS format, Scriptable using Python and other languages, and it shines with pros like Open source and free to use, Available on many platforms, Fast and robust performance, Supports integer programming, Can handle large models.

Feature	GNU Linear Programming Kit	lpsolve
Overall Score	N/A	N/A
Primary Category	Development	Development

Product Overview

GNU Linear Programming Kit

Description: The GNU Linear Programming Kit (GLPK) is an open-source software package for solving large-scale linear programming, mixed integer programming, and other related problems. It features a high-performance mathematical programming solver with data structures and algorithms to efficiently handle large problems.

lpsolve

Description: lpsolve is an open-source linear programming solver. It allows formulating linear optimization problems in a simple modeling language and solving them with either the revised simplex method or the primal-dual interior point method.

Key Features Comparison

GNU Linear Programming Kit Features

• Linear programming solver
• Mixed integer programming solver
• Network flow/graph optimization capabilities
• Support for writing models in GNU MathProg modeling language
• APIs for C, C++, Java, Python, OCaml, PHP, Ruby, R
• Command line tools glpsol for solving models
• Modeling language translator glpsol

lpsolve Features

• Formulate linear programming models
• Solve models with revised simplex method
• Solve models with primal-dual interior point method
• Handle integer variables
• Import/export models in MPS format
• Scriptable using Python and other languages

Pros & Cons Analysis

GNU Linear Programming Kit

Pros

• Free and open source
• High performance solver
• Support for large scale problems
• APIs for many programming languages
• Active development community

Cons

• Limited documentation and learning resources
• Not as user friendly as some commercial solvers
• Less features than some commercial alternatives

lpsolve

Pros

• Open source and free to use
• Available on many platforms
• Fast and robust performance
• Supports integer programming
• Can handle large models

Cons

• Limited documentation and support
• User interface is not very intuitive
• Does not support more advanced modeling features
• Not as full-featured as commercial solvers

Pricing Comparison

GNU Linear Programming Kit

• Open Source

lpsolve

• Open Source