Menu

Developer: LINDO Systems Inc.

Latest Release: What’sBest! 15, LINGO 17, LINDO API 11

Operating System: See system requirements for each module

LINDO Systems developed a collection of software packages that facilitate building and solving optimisation models.

Linear, non-linear and integer optimisation tools are used by companies interested in addressing questions related to profit maximisation, cost minimisation, production planning, transportation, finance, portfolio allocation, capital budgeting, blending, scheduling, inventory, resource allocation and other.

LINDO Systems offer the following products:

What’Best!: The Spreadsheet Solver

WhatsBest! is an add-in to Excel that allows you to build large scale optimisation models in a free form layout within a spreadsheet.

LINGO: Modelling Environment and Solver

LINGO combines a full featured modelling environment with a set of solvers for linear, integer and nonlinear models. LINGO comes with a DLL, which can be called from your own application.

LINGO API: Optimisation Engine

The LINDO API allows application developers to easily create customized programs that call LINDO’s set of linear and integer solvers. It includes dozens of routines to formulate, solve, query and modify optimization problems and gives the user access to greater speed and algorithmic control than any other product offered by LINDO.

Solver Suite

LINDO Systems bundle offering of all the above three products.

What’sBest! 15

What’sBest! 15 is currently a beta release (available for download here), see below for the new features in What’sBest! V15.

What’sBest! 15 included 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

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.

LINGO 17

Currently a beta release, LINGO 15 is available for download here. See below the new features contained in LINGO 17:

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 @AllDiff constraint for general integer variables. The @AllDiff 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.

Most Recent Modeling Language and Feature Enhancements:

  • New capability to pass arguments to user-defined procedures.
  • Support of data frame style input in Data and Calc sections has been added.
  • New functions for programmatically reading input data in Calc sections.
  • New function for retrieving the next best solution to a binary integer programming model. The function allows you to examine and/or display variable values and decide if further solutions should be generated, or it can be called repeatedly to iterate through all feasible solutions.
  • New function for displaying space time charts.
  • New functions for performing QR factorization of matrices and performing matrix multiplication.
  • Option for specifying the default starting point for variables.

LINDO API 11

Release 9 of LINDO API 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.

Several new functions and constraint types are recognized, e.g., the AllDiff constraint for general integer variables. AllDiff constraints allow 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.

What’sBest!

  • Windows 32x80

LINGO

  • Windows 32x86
  • Windows 64x86
  • Linux 32x86
  • Linux 64x86

LINDO API

  • Windows 32x86
  • Windows 64x86
  • Mac-PowerPC
  • Mac 32x86
  • Linux 32x86
  • Linux 64x86
  • Solaris-SPARC 32
  • Solaris-SPARC 64

Solver Suite

  • Windows 32x80

Coming Soon. Please email us at info@timberlake.co.uk to order your license

Post your comment

Timberlake Consultants