What's New in LINDO API 14.0

Version 14.0

What's New in LINDO API 14.0

Linear-Integer solver

  • Improved heuristics for general integer programs.
  • Average performance improvement of 2-3% on our standard test set.
  • Improved method for generating all alternative optima to a linear program:
    • The first call to LSgetNextBestSol() creates a prespecified number of corner points via pivoting on the optimal solution set.
    • Subsequent calls will nonredundantly return successive corner points.
    • Standard solution query methods can be used to access primal-dual vectors following each call to LSgetNextBestSol.


  • Support for Indicator constraints, e.g., z = 0 implies x + y <= 0;
  • More expressions can be automatically linearized, so you can now use a fast linear solver where otherwise a much slower nonlinear solver might be required.
  • Advanced linearization of QP and Conic models
  • Improved linearization of certain IF expressions.

Nonlinear and Global Solver

  • faster (order of magnitude) solution of linear fractional programs (ratio objectives).
  • improved bound tightening process in preprocessing of nonlinear models.
  • auxiliary variables generated automatically to improve performance with complicated expressions.
  • Support for additional useful but “problematic” functions: Power utility funktion (xg-1)/g and the exponential ratio function (exp(g) - 1)/g are important in some situations modeling consumer behavior. LINDO API can now robustly avoid the numerical problems that would otherwise occur when g approaches 0.


  • Julia/JuMP is now supported officially.
  • Python interface installations now easier via pip (pypi.org)
  • Matlab interface now has two alternative methods for linear and integer optimization, LSlinprog and LSintprog. Argument lists follow their counterparts, linprog and intprog, in Matlab’s optimization toolbox.