Makes the solving of stochastic, linear, nonlinear, quadratic, etc. integer optimization models quicker and more effective. It embeds in-built solvers, an environment for building and editing problems as well as a language for optimization models.
Lingo is a powerful modeling program that integrates features which can be used in a wide range of fields such as: mathematics, physics, economy, automatic control, finances, etc. It allows you to create various model types and generates accurate solutions for them. Lingo comes with its own modeling language and a comprehensive help manual.
As an Automatic Control and Computer Engineering graduate, I found Lingo to be an efficient alternative to other popular modeling applications such as MatLab. It uses few system resources (CPU, memory, etc.) and generates professional solutions for any type of model that the user provides. Lingo also includes its own sample models for various purposes. They include comments that help users understand each function or algorithm that is being used.
I should mention that Lingo is recommended for users that have advanced modeling knowledge. It requires at least basic understanding of modeling principles. By opening the integrated help manual, users can access detailed information regarding the program features. Also, it proves to be useful when it comes to learning about various functions and commands.
Students as well as professionals from many fields can use Lingo to create models and generate solution for various problems.
v18.0.0.56 [Dec 7, 2018]
- Better Performance on Linear Models with Improved Simplex Solvers: Enhancements to the Simplex solvers boost speed on linear models. Models solve an average of 18% faster using primal simplex and 15% faster for dual simplex.
- Significantly Faster on Large Quadratic Models: Improvements in handling large quadratic matrices, e.g. 1000 x 1000, provide substantial performance improvement solving financial portfolio and other quadratic models.
- Improved Handling of Models with Discontinuous Functions: Models that use discontinuous functions such as MOD(x,k), INT(x), ROUND(x), can be solved more quickly.
- Faster When Simultaneously Solving LPs Using Different Solvers: In situations in which it may be difficult to predict whether the Primal, Dual or Barrier Solver will provide the fastest solution to a linear model, an improved Multi-Core feature allows you to assign each solver to a separate core and run them concurrently. So, you are ensured the solution in the shortest time regardless of which solver is fastest.
- Multi-Start NLP Solver Now Supports a Target Value: Users can specify a target value for the objective function. As soon as any multi-start thread achieves a specified target all threads stop.
- Most Recent Modeling Language and Feature Enhancements:
- New chart functions: Gantt charts, stacked vertical bar, stacked horizontal bar.
- New function for executing commands from R statistics package from LINGO.
- Ability to interrupt solver in a CALC section, but continue execution of the CALC.
- New arithmetic functions: @SIGNPOWER, @LMTD and @RLMTD for heat exchanger and nonlinear network models.
- New solver log option: Enable the solver log, set its output level.
