![]() With this function, the package can be applied to substantive problems, relying on Mathematica's native code for intensive computation. In order to utilize Mathematica's efficient linear programming routine, we then develop a function that can deduce the final tableau from the Spartan output of ConstrainedMax. Examples of its use to solve a standard maximization problem, find multiple optimal feasible solutions, solve linear programming problems by the Big M method, and do a sensitivity analysis are included. Date: 1994 By: Carter, Michael, 1950-, University of Canterbury. The notebook simplex.ma contains a simplex command which produces a simplex tableau for a linear programming problem. Building on the foundation laid in the first part, we first develop a set of tools for sensitivity analysis of the optimal solution. The goal of our linear programming problem is to maximize a linear objective function f(x) cT x c1x1 + + cnxn on the convex polyhedron p. Linear programming with Mathematica / Michael Carter. ![]() Chapter 6 Sensitivity Analysis Introduction. This article, the second of two parts, describes a package designed to supplement Mathematica's linear programming facility. View Notes - Linear Programming- Note 10 from MATHEMATIC A at University of Colombo. Linear Programming with Mathematica: Sensitivity Analysis 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. In short: You rarely need to use clear all - most of the time a simple clear will be enough. Wolfram Data Framework Semantic framework for real-world data. mathematica clear all variables mathematica clear all variables.
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