
LINGO is an integrated optimization modeling software for linear, nonlinear, integer, and stochastic problems. It offers a powerful modeling language, built-in solvers, and seamless data integration with spreadsheets and databases, enabling fast, efficient development and analysis of complex mathematical models.
Vendor
LINDO Systems
Company Website


LINGO
LINGO is a powerful optimization modeling software designed to simplify and accelerate the development and solution of mathematical models. It supports a wide range of problem types including linear, nonlinear, integer, quadratic, stochastic, and global optimization. LINGO integrates a modeling language, development environment, and built-in solvers into a single package, making it ideal for analysts, researchers, and decision-makers across industries.
Features
- Intuitive Modeling Language: Express models using summations and subscripted variables in a readable, paper-like format.
- Integrated Solvers: Automatically selects and runs the appropriate solver for the model type, including simplex, barrier, nonlinear, global, and stochastic solvers.
- Data Connectivity: Imports and exports data directly from spreadsheets and databases for seamless integration.
- Interactive and Programmatic Use: Build and solve models interactively or call LINGO from external applications via DLL, OLE, or Excel macros.
- Multi-Core Processing: Utilizes multiple CPU cores for faster model generation and solution.
- Extensive Documentation: Comes with a comprehensive user manual and modeling textbook, plus dozens of sample models.
Capabilities
- Linear and Integer Programming: Solve large-scale LP and MIP problems with advanced preprocessing and cut generation.
- Nonlinear and Global Optimization: Use GRG, SLP, and branch-and-bound techniques to find local or global optima.
- Quadratic and Conic Models: Efficiently solve models with quadratic objectives or constraints, including SOCPs.
- Stochastic Programming: Model uncertainty with multistage stochastic optimization using Benders decomposition and deterministic equivalents.
- Model Reduction and Linearization: Automatically simplify models and convert nonsmooth functions into linear equivalents for faster solving.
Benefits
- Speed and Efficiency: Reduces development time and accelerates solution processes with built-in solvers and preprocessing.
- Flexibility: Handles a wide variety of optimization problems in a single environment.
- Ease of Use: Designed for both novice and expert users with intuitive syntax and extensive help resources.
- Scalability: Suitable for small models and large enterprise-scale optimization tasks.
- Integration: Easily connects with external applications and data sources for end-to-end decision support.