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Category: Business and Industry

Date Submitted: 03/01/2012 06:20 AM

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Lee White

E00335260

Dr. Yasin

MGMT 3050

Feb. 2, 2012

Linear Programming in Automotive Corporations

In the reading of this article the understanding of problems impacted with the automotive corporations in the real world are understood. The linear programming model is what is decided on the maximize cost throughout the logistic system. The model is in a mathematical form having objective functions of minimizing the path to which cars are sold or carried. In using the linear programming model we find the best answers in mathematical form and also in a short time length. The models also include a lot of variables throughout that nature interferes with.

In today’s decision making the linear programing model is used quite often. When dealing with the linear programming model various linear inequalities are taken, finding the best option given to nature’s conditions. Linear programming is a way to optimize for the best situation in the area of mathematics. A lot of variables can be in each when all the real life situations are taken into thought. Graphing inequalities is the major way in process of finding the linear-programming problems.

With the prices in gas making transportation a high cost, companies are focused on their logistics system. Logistics optimization is very important to keep prices down for sales. When we give mor operational and practical insights and provide innovative resolutions to logistics problems with the linear program. The first objective is minimizing the length of routes while also getting the maximum capacity in the trucks. The First step is dividing different areas into zones to classify what truck will deliver in the certain areas. If the number of zones is increased then the answer will be more précised. When loading cars the priority to trucks is varied on time and managerial viewpoints. Cars in the line usually have more time more priority. If cars are not loaded to trucks today then the probability will...

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