LINGO 16 Enhancements


Release 16 of LINGO 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 large linear models.

Large models solve an average of 35% faster using primal simplex and 20% faster for dual simplex.


Improved Integer Solver with new features

A new optimization mode has been introduced to ensure reproducibility of runs.

Investigate alternative optima more quickly. Enhancements to the K-Best algorithm allow finding K best solutions

in little more time than finding one solution.

Find faster solutions to models with knapsack constraints and block structures using new heuristic algorithms.

New preprocessing level tightens variable bounds for better performance on classes of nonlinear models.


Enhanced Stochastic Solver

Large linear multistage SP instances solve 60% faster with improved cut management for Nested Benders Decomposition Method.

Better handling of multistage SP models which do not have full-recourse.

Extensions to the parser allow the use of arbitrarily complex functions of stochastic parameters.


Improved Global Solver

Performance of Global solver has been dramatically improved on classes of quadratic problems. In particular, non-convex quadratic

problems rejected by other solvers, or otherwise solvable only slowly to a local optimum by traditional NLP solvers. Can solve some

previously intractable problems to global optimality, especially financial portfolio models with minimum buy quantities,

and/or limit on number of instruments at nonzero level.

Incorporates a new bound tightening process to the linearization procedure and improves solvability of linearized model.

Dramatically faster, more robust performance on many models with functions like @MAX( ), @MIN( ), @ABS( ), x*z where z = 0 or 1, etc.


Native Macintosh and Linux Support

LINGO's user interface has been entirely rewritten to offer native support for the Macintosh and Linux platforms.

Below is an image of the Mac version running a small nonlinear program.

Lingo Model on a Mac

Matrix Functions:

There have been a number of new functions were added to LINGO for performing matrix operations.

Supported operations include: eigenvalues and eigenvector computation, matrix determinant, Cholesky factorization,

matrix inverse, and matrix transpose.


Linear Regression:

The new @REGRESS function for multiple linear regression has been added.


Other Improvements:

Tornado charts now supported.

Additional sorting capabilities, convenient for data preparation and solution reporting.

A new date function, @STM2YMDHMS, for converting LINGO's standard time values into the equivalent calendar date and time.