Sensitivity Analysis in Linear Programming with Real Application

Abstract

linear programming occupies at the present time a prominent place in different areas and have wide applications, where lies its importance as a means of studying the behavior of a large number of systems as well as it is the simplest and easiest types of models that can be created to handle the dilemmas of industries and commercial, military, and other In this paper, we treated with the solution post optimality or as it's known Sensitivity Analysis by using the principle of Shadow Prices, The scientific solution to any problem not be a complete solution as soon as access to the best solution, That any change in the model (constants values) or what is known as input data will change the linear programming problem and will affect the best solution and we need to methods to help us in the style of standing on the effect of changing these constants on the best solution tastiest reached It was addressed general concepts of dual model and Some theories of sensitivity analysis, we take real data from The Texago Corporation is a large, fully integrated petroleum company based in the U.S.A., formulated the mathematical model and obtain the optimal results by package winqsb and finally calculated the Shadow Prices for binding constraints, Add to the above stated, we reviewed in this paper linear programming model under fuzzy environment and use a new method based on prime numbers