Overview of Multi-Objective Optimization using Evolutionary Algorithms Book

Evolutionary algorithms are relatively new, but very powerful techniques used to find solutions to many real-world search and optimization problems. Many of these problems have multiple objectives, which leads to the need to obtain a set of optimal solutions, known as effective solutions. It has been found that using evolutionary algorithms is a highly effective way of finding multiple effective solutions in a single simulation run. Special Features ?ú Includes many applications to real-world problems such as engineering design and scheduling. ?ú Provides discussions of advanced topics and future research. ?ú Contains exercises and solutions to enhance the material. ?ú Written in way that is accessible to those with limited knowledge of classical multi-objective optimization and evolutionary algorithms. Table of Content Foreword. Preface. Prologue. ?ú Multi-Objective Optimization. ?ú Classical Methods. ?ú Evolutionary Algorithms. ?ú Non-Elitist Multi-Objective Evolutionary Algorithms. ?ú Elitist Multi-Objective Evolutionary Algorithms. ?ú Constrained Multi-Objective Evolutionary Algorithms. ?ú Salient Issues of Multi-Objective Evolutionary Algorithms. ?ú Applications of Multi-Objective Evolutionary Algorithms. Epilogue. References. Index.

• Book Type :

ComputerScience

• Book Binding :

Paperback

• Language :

English

• Number of Pages :

536 pages

• ISBN - 10 :

8126528044

• Multi-Objective Optimization using Evolutionary Algorithms Published On :

7-Sep-10

• Resource:

Computing, Internet & DigitalMedia, ComputerScience for Students and Professionals

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