Using linear programming sensitivity analysis to solve generalized linear programming problems

• Main Authors: Cristobal, Beverly V., Guilatco, Crispin Vicente P.
• Format: text
• Language: English
• Published: Animo Repository 1996
• Subjects: Linear programming; Linear operators > Generalized inverses; Programming (Mathematics); Simplexes (Mathematics); Problem solving
• Online Access: https://animorepository.dlsu.edu.ph/etd_bachelors/16299
• Institution: De La Salle University

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).