Optimization in Operations Research
Published on 5. August 1997
Book
Paperback/Softback
919 pages
978-0-02-398415-0 (ISBN)
Description
This book is specifically designed to change the way deterministic optimization is taught to introductory students. KEY TOPICS: Toward this end, it exposes students to the broad scope of the topic, reinforces the basic principles, sparks students' enthusiasm about the field, provides tools of immediate relevance and develops the skills necessary to use those tools.
More details
Language
English
Place of publication
United States
Publishing group
Pearson Education (US)
Target group
College/higher education
Dimensions
Height: 222 mm
Width: 174 mm
Thickness: 46 mm
Weight
1462 gr
ISBN-13
978-0-02-398415-0 (9780023984150)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
New editions
Ronald L. Rardin
Optimization in Operations Research
Book
04/2016
2nd Edition
Pearson
€273.58
Article exhausted; check different version
Ronald L. Rardin
Optimization in Operations Research
Book
02/2016
2nd Edition
Pearson
€156.17
Article is exhausted; no reprint
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.