'Simplex algorithm' diaporamas de présentation

Duality Theory

Duality Theory. LI Xiaolei. Finding the dual of an LP. When taking the dual of a given LP, we refer to the given LP as the primal. If the primal is a max problem, the dual will be a min problem, and vice versa.

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Session 1a

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Instructor: Shengyu Zhang

CSC3160: Design and Analysis of Algorithms. Week 6: Linear Programming. Instructor: Shengyu Zhang. LP. Motivating examples Introduction to algorithms Simplex algorithm On a particular example General algorithm Duality An application to game theory. Example 1: profit maximization.

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Linear Programming Reading: CLRS, Ch. 29 or reference

Linear Programming Reading: CLRS, Ch. 29 or reference. CSE 6331 Algorithms Steve Lai. Simplex Method. A system of linear inequalities defines a polytope (or simplex) as a feasible region.

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Simplex method convergence

Simplex method convergence. Convergence when the problem is non degenerate. Non degeneracy assumption: all the basic variables are stricly positive at each iteration Theorem : Consider a linear programming problem in standard form.

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Machine Learning Based Models for Time Series Prediction

Machine Learning Based Models for Time Series Prediction. 2014/3. Outline. Support Vector Regression Neural Network Adaptive Neuro -Fuzzy Inference System Comparison. Support Vector Regression. Basic Idea Given a dataset

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Degeneracy and the Convergence of the Simplex Algorithm

Degeneracy and the Convergence of the Simplex Algorithm. LI Xiao-lei. Preview. The relationship (for a max problem) between the z-values for the current bfs and the new bfs:

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MA5233: Computational Mathematics

MA5233: Computational Mathematics Weizhu Bao Department of Mathematics & Center for Computational Science and Engineering National University of Singapore Email: bao@math.nus.edu.sg URL: http://www.math.nus.edu.sg/~bao Computational Science Third paradigm for Discovery in Science

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MA5233: Computational Mathematics

MA5233: Computational Mathematics. Weizhu Bao Department of Mathematics & Center for Computational Science and Engineering National University of Singapore Email: bao@math.nus.edu.sg URL: http://www.math.nus.edu.sg/~bao. Computational Science. Third paradigm for

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Chapter 6 Simplex Method

Chapter 6 Simplex Method. 6.1 Solving Linear Equations Using Row Operations 6.2 The Canonical Augmented Matrix 6.3 Updating the Augmented Matrix 6.4 The Simplex Algorithm

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Optimization

Optimization. Issues. What is optimization? What real life situations give rise to optimization problems? When is it easy to optimize? What are we trying to optimize? What can cause problems when we try to optimize? What methods can we use to optimize?. One-Dimensional Minimization.

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The Simplex Algorithm Spring 2013-14

The Simplex Algorithm Spring 2013-14. Eastern Mediterranean University IENG511Optimization Theory. Introduction. In many industrial applications, the simplex algorithm is used to solve LPs with thousands of constraints and variables. The two-variable LP program can be solved graphically.

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M-Method

M-Method. The M-Method starts with LP in equation form. An equation i that does not have a slack (or a variable that can play the role of a slack) is augmented with an artificial variable, Ri , to form a starting solution similar to all slake basic solution. . E xample. Minimize z=4x1+x2

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Flow Network Models for Sub-Sentential Alignment

Flow Network Models for Sub-Sentential Alignment . Ying Zhang (Joy) Advisor: Ralf Brown Dec 18 th , 2001. Background. Sub-sentential alignment problem Given a bilingual parallel sentence pair, to find the correspondence between source words and target words

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July 18-19, 2013 2013 New Orleans Stata Conference

Mathematical Optimization in Stata : LP and MILP. July 18-19, 2013 2013 New Orleans Stata Conference. ?. Choonjoo Lee Korea National Defense University bloom.rampike@gmail.com. CONTENTS . I. Motivation. II. Taxonomy of Mathematical Optimization. III.

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Operations Management Professor Beril Toktay Operations Management Group College of Management Georgia Tech

Operations Management Professor Beril Toktay Operations Management Group College of Management Georgia Tech. Who Am I?. BS in Industrial Engineering & Math from Bosphorus University. MS in Industrial Engineering from Purdue University. PhD in Operations Research from MIT.

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Unrestricted-in-Sign Variables

Unrestricted-in-Sign Variables.

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CS 312: Algorithm Analysis

This work is licensed under a Creative Commons Attribution-Share Alike 3.0 Unported License . CS 312: Algorithm Analysis. Lecture # 31: Linear Programming: the Simplex Algorithm, part 2. Slides by: Eric Ringger, with contributions from Mike Jones and Eric Mercer. Announcements.

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Local search algorithms

Local search algorithms. Most local search algorithms are based on derivatives to guide the search. For differentiable function it has been shown that even if you need to calculate derivatives by finite differences, derivative-based algorithms are better than ones that do not use derivatives.

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