Linear Programming: An Introduction
Edition: 1
Copyright: 2019
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Linear Programming: An Introduction examines mathematical methods used to model, analyze, and solve decision-making problems involving limited resources and competing objectives. The course introduces linear programming concepts, including problem formulation, linear algebra foundations, graphical solutions, simplex methods, and advanced techniques for handling constraints and special conditions. The material explores optimization strategies such as dual programming, sensitivity analysis, transportation models, and integer programming. These concepts demonstrate how mathematical models can be applied to improve resource allocation, operational efficiency, planning, and decision-making in engineering, business, and other fields.
Chapter 1 Formulation of a Linear Programming Problem
Chapter 2 Review of Linear Algebra
Chapter 3 Solving a Linear Programming Using the Graphical Method
Chapter 4 Simplex Methods for Solving a Linear Programming Problem
Chapter 5 Big M and Two-Phase Methods
Chapter 6 Special Conditions in Linear Programming Problem
Chapter 7 Dual Programming
Chapter 8 Sensitivity Analysis of a Linear Programming
Chapter 9 Transportation Problems
Chapter 10 Integer Programming
Bibliography
Shokoufeh Mirzaei, PhD is Chair and Professor of Industrial and Manufacturing Engineering at California State Polytechnic University, Pomona (Cal Poly Pomona). She earned her PhD in Industrial Engineering with a minor in Statistics and Probability from Wichita State University, along with master’s and bachelor’s degrees in Industrial and System Engineering from Isfahan University of Technology and Iran University of Science and Technology. Dr. Mirzaei’s research focuses on machine learning, big data analytics, applied optimization, systems engineering, and quality control.