Operations Research

Operations Research: A Practical Introduction offers a hands-on approach to the field of operations research (OR) and a useful guide for using OR techniques in scientific decision making, design, analysis and management. It provides readers with an introduction to standard mathematical models and algorithms.

Operations Research: A Practical Introduction is just that: a hands-on approach to the field of operations research (OR) and a useful guide for using OR techniques in scientific decision making, design, analysis and management. The text accomplishes two goals. First, it provides readers with an introduction to standard mathematical models and algorithms. Second, it is a thorough examination of practical issues relevant to the development and use of computational methods for problem solving. **

Highlights:

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• All chapters contain up-to-date topics and summaries

• A succinct presentation to fit a one-term course

• Each chapter has references, readings, and list of key terms

• Includes illustrative and current applications

• New exercises are added throughout the text

• Software tools have been updated with the newest and most popular software

Many students of various disciplines such as mathematics, economics, industrial engineering and computer science often take one course in operations research. This book is written to provide a succinct and efficient introduction to the subject for these students, while offering a sound and fundamental preparation for more advanced courses in linear and nonlinear optimization, and many stochastic models and analyses.

It provides relevant analytical tools for this varied audience and will also serve professionals, corporate managers, and technical consultants.

Autorentext
Michael Carter, Camille C. Price, Ghaith Rabadi

Inhalt

Table of Contents Chapter 1: INTRODUCTION TO OPERATIONS RESEARCH; Chapter 2: LINEAR PROGRAMMING; Chapter 3: NETWORK ANALYSIS; Chapter 4: INTEGER PROGRAMMING; Chapter 5: NONLINEAR OPTIMIZATION; Chapter 5: MARKOV PROCESSES; Chapter 6: QUEUING MODELS; Chapter 7: SIMULATION; Chapter 8: DECISION ANALYSIS; Chapter 9: HEURISTIC TECHNIQUES FOR OPTIMIZATION; Chapter 10: LOCAL SEARCH AND CONSTRUCTIVE HEURISTICS; Chapter 11: METAHEURISTICS; APPENDIX: Review of Essential Mathematics