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.