Goh Saito

Graduation Semester and Year

2012

Language

English

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Industrial Engineering

Department

Industrial and Manufacturing Systems Engineering

First Advisor

Herbert W Corley

Abstract

Simplex pivoting algorithms remain the dominant approach to solve linear programming (LP) because they have advantages over interior-point methods. However, current simplex algorithms are often inadequate for solving a large-scale LPs because of their insufficient computational speeds. This dissertation develops the significantly faster simplex-based, active-set approaches called Constraint Optimal Selection Techniques (COSTs). COSTs specify a constraint-ordering rule based on constraints' likelihood of being binding at optimality, as well as a rule for adding constraints. In particular, new techniques for adding multiple constraints in an active-set framework, and an efficient constraint-ordering rule for LP are proposed. These innovations greatly reduce computation time to solve LP problems.

Disciplines

Engineering | Operations Research, Systems Engineering and Industrial Engineering

Comments

Degree granted by The University of Texas at Arlington

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