Multi Objective Optimization using Evolutionary Algorithms

Evolutionary algorithms are relatively new, powerful techniques used to find solutions to many real--world search and optimization problems. Focusing on these "thinking" algorithms, this book offers comprehensive coverage of these techniques, which are highly effective in finding multiple effective solutions in a single simulation run. Evolutionary algorithms are very powerful techniques used to find solutions to 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. Comprehensive coverage of this growing area of research Carefully introduces each algorithm with examples and in-depth discussion Includes many applications to real-world problems, including engineering design anf scheduling Accessible to those with limited knowledge of multi-objective optimization and evolutionary algorithms This integrated presentation of theory, algorithms and examples will benefit those working and researching in the areas of optimization, optimal design anf evolutionary computing. "Deb's book is complete, eminently readable, and the coverage is scholarly and thorough. It is my pleasure and duty to urge you to buy this book, read it, use it and enjoy it." —David E. Goldberg, University of Illinois at Urbana-Champaign, USA

Pagina's: 536, Editie: Eerste editie, Hardcover, John Wiley & Sons