Operations Research: Principles and Practice / Edition 2

Operations Research: Principles and Practice / Edition 2

ISBN-10:
0471086088
ISBN-13:
9780471086086
Pub. Date:
01/16/1991
Publisher:
Wiley
ISBN-10:
0471086088
ISBN-13:
9780471086086
Pub. Date:
01/16/1991
Publisher:
Wiley
Operations Research: Principles and Practice / Edition 2

Operations Research: Principles and Practice / Edition 2

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Overview

Totally revised, this 2nd Edition includes a new chapter on decision analysis, and additional material on computer solutions of linear programming problems, LP applications, the use of sensitivity analysis output, minimal spanning tree, goal programming, network of queues, and more. Throughout, mathematics is kept to an intermediate level.

Product Details

ISBN-13: 9780471086086
Publisher: Wiley
Publication date: 01/16/1991
Edition description: REV
Pages: 656
Product dimensions: 7.17(w) x 10.16(h) x 1.36(d)

About the Author

A. "Ravi" Ravindran, is Professor and Director of the School of Industrial Engineering at the University of Oklahoma, Norman. He received a B.S. degree in electrical engineering from Birla Institute of Technology and Science, Pilani (India), and MS and Ph.D. in Industrial Engineering and Operations Research from the University of California are Berkeley.

Don T. Phillips is Professor of Industrial Engineering at Texas A & M University, College Station, Texas. He received his Bachelor of Science degree in Industrial Engineering from Lamar University in 1965 and a Ph.D. in Industrial Engineering from the University of Arkansas in 1968.

James J. Solberg is Professor of Industrial Engineering at Perdue University, West Lafayette, Indiana. He received a B.A. degree from Harvard University in Mathematics in 1964, a M.A. in mathematics and a M.S. in Industrial Engineering from the University of Michigan in 1967, and a Ph.D. in Industrial Engineering from the University of Michigan in 1969.

Table of Contents

The Nature of Operations Research.

Linear Programming.

Network Analysis.

Advanced Topics in Linear Programming.

Decision Analysis.

Random Processes.

Queueing Models.

Inventory Models.

Simulation.

Dynamic Programming.

Nonlinear Programming.

Appendices.

Index.
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