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John W. Chinneck - Feasibility and Infeasibility in Optimization: - 9781441945198 - V9781441945198
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Feasibility and Infeasibility in Optimization:

€ 116.71
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Description for Feasibility and Infeasibility in Optimization: Paperback. Series: International Series in Operations Research & Management Science. Num Pages: 274 pages, black & white illustrations. BIC Classification: PBU. Category: (P) Professional & Vocational. Dimension: 234 x 156 x 15. Weight in Grams: 456.

Feasibility and Infeasibility in Optimization is an expository book focused on practical algorithms related to feasibility and infeasibility in optimization. Part I addresses algorithms for seeking feasibility quickly, including recent algorithms for the difficult cases of nonlinear and mixed-integer programs. Part II provides algorithms for analyzing infeasibility by isolating minimal infeasible (or maximum feasible) subsets of constraints, or by finding the best repair for the infeasibility. Part III describes surprising applications in areas such as classification, computational biology, and medicine. Connections to constraint programming are shown. A main goal is to impart an understanding of the methods so that practitioners ... Read more

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Product Details

Format
Paperback
Publication date
2010
Publisher
Springer-Verlag New York Inc. United States
Number of pages
274
Condition
New
Series
International Series in Operations Research & Management Science
Number of Pages
274
Place of Publication
New York, NY, United States
ISBN
9781441945198
SKU
V9781441945198
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15

Reviews for Feasibility and Infeasibility in Optimization:
From the reviews: "This book is really the first monograph to summarize the growing body of research on the analysis of feasibility and infeasibility of optimization problems. With up to date coverage and very thorough bibliography, it will be of definite interest to researchers working in this area. The book may also be of interest ... Read more

Goodreads reviews for Feasibility and Infeasibility in Optimization:


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