Optimization in Operations Research
International Edition
Published on 19. August 1997
Book
Paperback/Softback
919 pages
978-0-13-281925-1 (ISBN)
Description
For first courses in operations research, operations management.
Covers a broad range of optimization techniques, including linear programming, network flows, integer/combinational optimization, and nonlinear programming. Emphasizes the importance of modeling and problem formulation, this text teaches students how to apply algorithms to real-world problems to arrive at optimal solutions.
Visit the author-maintained web site athttp://comp.uark.edu/~rrardin/oorbook
Covers a broad range of optimization techniques, including linear programming, network flows, integer/combinational optimization, and nonlinear programming. Emphasizes the importance of modeling and problem formulation, this text teaches students how to apply algorithms to real-world problems to arrive at optimal solutions.
Visit the author-maintained web site athttp://comp.uark.edu/~rrardin/oorbook
More details
Language
English
Place of publication
United States
Publishing group
Pearson Education (US)
Target group
Professional and scholarly
Dimensions
Height: 177 mm
Width: 234 mm
Thickness: 36 mm
Weight
1315 gr
ISBN-13
978-0-13-281925-1 (9780132819251)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Other editions
New editions
Ronald Rardin | Ronald L. Rardin
Optimization in Operations Research
Pearson New International Edition
Book
11/2013
1st Edition
Pearson Education Limited
€110.99
Shipment within 10-20 days
Content
1. Problem Solving with Mathematical Models.
2. Deterministic Optimization Models in Operations Research.
3. Improving Search.
4. Linear Programming Models.
5. Simplex Search for Linear Programming.
6. Interior Point Methods for Linear Programming.
7. Duality and Sensitivity in Linear Programming.
8. Multiobjective Optimization and Goal Programming.
9. Shortest Path and Discrete Dynamic Programming.
10. Network Flows.
11. Discrete Optimization Models.
12. Discrete Optimization Methods.
13. Unconstrained Nonlinear Programming.
14. Constrained Nonlinear Programming.
2. Deterministic Optimization Models in Operations Research.
3. Improving Search.
4. Linear Programming Models.
5. Simplex Search for Linear Programming.
6. Interior Point Methods for Linear Programming.
7. Duality and Sensitivity in Linear Programming.
8. Multiobjective Optimization and Goal Programming.
9. Shortest Path and Discrete Dynamic Programming.
10. Network Flows.
11. Discrete Optimization Models.
12. Discrete Optimization Methods.
13. Unconstrained Nonlinear Programming.
14. Constrained Nonlinear Programming.