LINDO API 6.1 includes new features to allow users to incorporate uncertainty into their optimization models as well as solver enhancements to the Linear, Integer and Global solvers.

New Stochastic Programming Option

New features allow modeling and optimization for models with uncertain elements via multistage stochastic linear, nonlinear and integer stochastic programming (SP). Benders decomposition is used for solving large linear SP models. Deterministic equivalent method is used for solving nonlinear and integer SP models. Support is available for over 20 distribution types (discrete or continuous). User defined functions are allowed via call-backs. Customized sampling scenarios via 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 uniform generation via a choice of three different generators.

Faster Linear Solvers

Large linear models solve an average of 20% faster with improved Primal and Dual Simplex solvers.

Substantial Integer Solver Improvements

The Integer Solver is an average of 50% faster on a broad range of integer models. Substantial improvements have been made to all heuristics for finding close to optimal solutions quickly. There have also been significant improvements in cut generation for certain types of special model structures.

Global Solver Improvements

The Global Solver has seen significant improvement in the handling of nonlinear models with quadratic terms, especially non-convex quadratic expressions.

For general information on LINDO API's capabilities, visit our LINDO API product page. To try a limited capacity version of LINDO API, see our download page. To order a copy of LINDO API or update an older version, go to our order page.

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