Using linear programming sensitivity analysis to solve generalized linear programming problems
Date of Publication
1996
Document Type
Bachelor's Thesis
Degree Name
Bachelor of Science in Mathematics
College
College of Science
Department/Unit
Mathematics and Statistics
Abstract/Summary
This research work presents a comprehensive discussion of linear programming and the simplex method. Linear programming is a mathematical method of allocating limited resources in order to maximize some measure of performance or minimize some measure of cost, in which the measure of performance or cost is a linear function and the restrictions on the availability or utilization of resources is expressed as linear equations or inequalities. The simplex method is a method that is used to solve linear programming problems. It has also played an important role in the development of solution methods for nonlinear optimization problems. The standard parametric analysis techniques of the simplex method can also be applied to solve nonclassical generalized linear programs. This extension of the applications of the simplex method is mentioned in this work.This algorithm was formulated by Emmanuel Macalalag and Moshe Sniedovich in their paper Generalized Linear Programming and Sensitivity Analysis Technique Naval Research Logistics, Vol. 43, pp. 397-413 (1996).
Abstract Format
html
Language
English
Format
Accession Number
TU07444
Shelf Location
Archives, The Learning Commons, 12F, Henry Sy Sr. Hall
Physical Description
72 leaves
Keywords
Linear programming; Linear operators--Generalized inverses; Programming (Mathematics); Simplexes (Mathematics); Problem solving
Recommended Citation
Cristobal, B. V., & Guilatco, C. P. (1996). Using linear programming sensitivity analysis to solve generalized linear programming problems. Retrieved from https://animorepository.dlsu.edu.ph/etd_bachelors/16299