NETWORK OPTIMIZATION USING LINEAR PROGRAMMING AND REGRESSION
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The purpose of this research is to explore the synergistic application of linear programming, regression, and computer science to solve practical economic problems. In particular, this research focuses on network optimization problems in which the aim is to maximize revenue and minimize production, transportation, and other costs by using historical information to predict future market behavior. The first half of the thesis provides background information on linear programming and regression for readers who may not be familiar with the subjects. The remaining sections of this thesis cover the modeling process and computer programming design, where the variables of interest are identified, arranged into an appropriate form, and MATLAB programming is utilized to carry out linear programming and regression operations to provide an optimized solution for the network using given historical data and market conditions.