![]() The last package may be used to transform a general two-stage program into a multi-stage stochastic program of any size. ![]() These functions, organized into "packages," are divided into three categories: packages used for deterministic linear programming, packages used for stochastic programming, and a package which may be used to manipulate LPs and SPs. The Wolfram Language has a collection of algorithms for solving linear optimization problems with real variables, accessed via LinearOptimization, FindMinimum, FindMaximum, NMinimize, NMaximize, Minimize and Maximize. ![]() This report describes several Mathematica functions which may be of use in mathematical programming, and in particular, stochastic programming. Linear optimization problems are defined as problems where the objective function and constraints are all linear. The Mathematica language is well suited for algorithmic prototyping and model manipulation. With nearly 6,000 carefully integrated, built-in functions delivering computation and knowledge, there's lots to learn about the Wolfram Language. Mathematica is a widely used computer software system for computational mathematics which is easily programmable in a higher level language than either Fortran or C. for Programmers Spend a few minutes with this tutorial to get up to speed with the foundations of the Wolfram Language. University of Michigan, Department of Industrial and Operations Engineering Technical Report 93-26 Selected Mathematica Tools for Mathematical Programming Finance, Statistics & Business Analysisįor the newest resources, visit Wolfram Repositories and Archives ».Wolfram Knowledgebase Curated computable knowledge powering Wolfram|Alpha. Wolfram Universal Deployment System Instant deployment across cloud, desktop, mobile, and more. Wolfram Data Framework Semantic framework for real-world data. ![]()
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