Operations Research Models and Methods
October 2002, ©2003
Bridging the gap between theory and practice, the author presents the quantitative tools and models most important to understanding modern operations research. You'll come to appreciate the power of OR techniques in solving real-world problems and applications in your own field. You'll learn how to translate complex situations into mathematical models, solve models and turn models into solutions. This text is designed to bridge the gap between theory and practice by presenting the quantitative tools and models most suited for modern operations research. The principal goal is to give analysts, engineers, and decision makers a larger appreciation of their roles by defining a common terminology and by explaining the interfaces between the underlying methodologies.
- Divides each subject into methods and models, giving you greater flexibility in how you approach the material.
- Concise and focused presentation highlights central ideas.
- Many examples throughout the text will help you better understand mathematical material.
Linear Programming Models.
Linear Programming Methods.
Sensitivity Analysis, Duality, and Interior Point Methods.
Network Flow Programming Models.
Network Flow Programming Methods.
Integer Programming Models.
Integer Programming Methods.
Nonlinear Programming Models.
Nonlinear Programming Methods.
Models for Stochastic Processes.
Discrete-Time Markov Chains.
Mathematics of Discrete-Time Markov Chains.
Continuous-Time Markov Chains.
Mathematics of Continuous-Time Markov Chains.
Queuing Networks and Decision Models.
- Excel add-ins - Almost all of the examples in the text are solved with Excel.
- Comprehensive Website - An abundance of teaching material exists on the website. The interactive tools can be used to re-enforce procedures taught in class, and an alternative teaching source is available to relieve the instructor of demonstrating procedures to students who are having difficulty with the material.
- Concise and Focused Presentation - Central ideas are easily located throughout the text, saving the student time from wading through unnecessary information. This also allows the instructor to focus on the core material of a topic without getting sidetracked.
- Examples and exercises throughout text use real data and real engineering situations. This motivates students to learn new concepts and gives them a taste of practical engineering experience.