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.
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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.
