• Announcing What'sBest 18, LINGO 20 and LINDO® API 14 releases with faster solvers and new features.

    Announcing What'sBest 18, LINGO 20 and LINDO® API 14 releases with faster solvers and new features.

  • What'sBest! 18 - Excel Add-In for Linear, Nonlinear, and Integer Modeling and Optimization

    What'sBest! 18 - Excel Add-In for Linear, Nonlinear, and Integer Modeling and Optimization

  • LINGO 20 - Optimization Modeling Software for Linear, Nonlinear, and Integer Programming

    LINGO 20 - Optimization Modeling Software for Linear, Nonlinear, and Integer Programming

  • LINDO® API 14 - Powerful Library of Optimization Solvers and Mathematical Programming Tools

    LINDO® API 14 - Powerful Library of Optimization Solvers and Mathematical Programming Tools

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  • What'sBest!

    What'sBest! lets you build linear, nonlinear, and integer models in Excel. Models are easy to build and understand using standard spreadsheet equations.


  • LINGO

    LINGO is a comprehensive tool designed to help you build and solve linear, optimization models quickly, easily, and efficiently.



  • LINDO® API

    LINDO® API creates optimization applications. It allows you to plug the power of the LINDO® solver right into customized applications that you have written.


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What’sBest! 15 includes a wide range of performance enhancements and new features.

 

Faster Solutions on Linear Models with Improved Simplex Solver

Enhancements to the Simplex solvers boost performance on linear models. Large models solve an average of 20% faster using primal simplex and 15% faster for dual simplex.

 

Improved Integer Solver

New symmetry detection capabilities dramatically reduce the time required to prove optimality on certain classes of models with integer variables. Performance has been improved on Markowitz portfolio problems with minimum buy quantities, and/or limit on number of instruments at nonzero level. Other enhancements provide faster solutions on certain task assignment-like models.

 

Global Solver Enhancements

Stability and robustness of the Global solver has been improved through several enhancements to quadratic recognition and range reduction. Improved exploitation of convexity of certain ratio constraints, e.g., as found in heat exchanger network design problems.

 

More Constraint Types Supported

Several new functions and constraint types are recognized, e.g., the =WBALLDIFF() All Different constraint, for general integer variables. The =WBALLDIFF() function allows one to specify a set of integer variables, such that each variable in the set must have a unique value, different from all other variables in the set.

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