LINDO API includes features to allow users to incorporate uncertainty into their optimization models.

Stochastic Programming Interface

·         Modeling and optimization with uncertain elements through multistage linear, nonlinear and integer stochastic programming (SP).

·         Extensive set of API functions to setup and solve SP models.

·         Benders decomposition for solving linear SP models.

·         Deterministic equivalent method for solving nonlinear and integer SP models.

·         Supports most (20+) parametric (continuous or discrete) distributions.

·         User-defined distribution functions to be used through callbacks.

·         Customized sampling scenarios through the statistical sampling API.

Statistical Sampling API

·         Extensive API functions to sample directly from various statistical distributions,

·         Variance reduction with Latin-Hyper-Cube and Anti-thetic variates sampling,

·         Generation of correlated samples via Pearson, Spearman, or Kendall correlation measures.

·         Pseudo random number generation via a choice of three different generators.

Simplex Solver Improvements

·        Large linear models solve an average of 20% faster with improved primal and dual solvers.

MIP Solver Improvements

·        Substantial improvements in all heuristics for finding close to optimal solutions quickly.

·        Significant improvements in cuts for certain types of special model structures.

Global Solver Improvements

·        Significant improvement in the handling of nonlinear models with quadratic terms, especially non-convex quadratic expressions.