LINDO vs lpsolve

Struggling to choose between LINDO and lpsolve? Both products offer unique advantages, making it a tough decision.

LINDO is a Office & Productivity solution with tags like linear-programming, integer-programming, optimization, mathematical-modeling.

It boasts features such as Linear programming solver, Nonlinear programming solver, Integer programming solver, Stochastic programming capabilities, Sensitivity analysis, What-if analysis and pros including Fast and efficient solver, Can handle large, complex optimization problems, Wide range of modeling capabilities, User-friendly interface, Good technical support.

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	LINDO	lpsolve
Overall Score	N/A	N/A
Primary Category	Office & Productivity	Development

Product Overview

LINDO

Description: LINDO is optimization software used for linear, nonlinear, and integer programming. It allows users to formulate mathematical models, solve them, and analyze the results. LINDO is known for its speed and ability to handle large, complex 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

LINDO Features

• Linear programming solver
• Nonlinear programming solver
• Integer programming solver
• Stochastic programming capabilities
• Sensitivity analysis
• What-if analysis

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

LINDO

Pros

• Fast and efficient solver
• Can handle large, complex optimization problems
• Wide range of modeling capabilities
• User-friendly interface
• Good technical support

Cons

• Steep learning curve
• Expensive licensing costs
• Limited customization options
• Not open source

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

LINDO

• Subscription-Based

lpsolve

• Open Source