Handbook of Test Problems in Local and Global Optimization

Floudas, Christodoulos A.; Pardalos, Panos M.; Adjiman, Claire S.; Esposito, William R.; Gumus, Zeynep H.; Harding, Stephen T.; Klepeis, John L.; Mey

ISBN 10: 0792358015 / ISBN 13: 9780792358015

Published by Kluwer Academic Publishers, 1999

About this Item

Presents a collection of test problems arising in literature studies and a wide spectrum of applications. This book is suitable for academic and industrial researchers interested in algorithmic and software development of well-designed nonconvex optimization test problems. Series: Nonconvex Optimization and Its Applications. Num Pages: 458 pages, biography. BIC Classification: TDC. Category: (P) Professional & Vocational. Dimension: 235 x 155 x 25. Weight in Grams: 818. . 1999. Hardback. . . . . Books ship from the US and Ireland.

Seller Inventory # V9780792358015

Bibliographic Details

• Title: Handbook of Test Problems in Local and Global Optimization
• Publisher: Kluwer Academic Publishers
• Publication Date: 1999
• Language: English
• ISBN 10: 0792358015
• ISBN 13: 9780792358015
• Binding: Hardcover
• Condition: New

About this title

Synopsis

Significant research activities have taken place in the areas of local and global optimization in the last two decades. Many new theoretical, computational, algorithmic, and software contributions have resulted. It has been realized that despite these numerous contributions, there does not exist a systematic forum for thorough experimental computational testing and· evaluation of the proposed optimization algorithms and their implementations. Well-designed nonconvex optimization test problems are of major impor­ tance for academic and industrial researchers interested in algorithmic and software development. It is remarkable that eventhough nonconvex models dominate all the important application areas in engineering and applied sci­ ences, there is only a limited dass of reported representative test problems. This book reflects our long term efforts in designing a benchmark database and it is motivated primarily from the need for nonconvex optimization test problems. The present collection of benchmarks indudes test problems from literature studies and a large dass of applications that arise in several branches of engineering and applied science.