Multi-Objective Optimization Using Evolutionary Algorithms

Multi-Objective Optimization Using Evolutionary Algorithms

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Evolutionary algorithms are relatively new, but very powerfultechniques used to find solutions to many real-world search andoptimization problems. Many of these problems have multipleobjectives, which leads to the need to obtain a set of optimalsolutions, known as effective solutions. It has been found thatusing evolutionary algorithms is a highly effective way of findingmultiple effective solutions in a single simulation run. Comprehensive coverage of this growing area of research Carefully introduces each algorithm with examples and in-depthdiscussion Includes many applications to real-world problems, includingengineering design and scheduling Includes discussion of advanced topics and future research Can be used as a course text or for self-study Accessible to those with limited knowledge of classicalmulti-objective optimization and evolutionary algorithms The integrated presentation of theory, algorithms and exampleswill benefit those working and researching in the areas ofoptimization, optimal design and evolutionary computing. This textprovides an excellent introduction to the use of evolutionaryalgorithms in multi-objective optimization, allowing use as agraduate course text or for self-study.This text provides an excellent introduction to the use of evolutionary algorithms in multi-objective optimization, allowing use as a graduate course text or for self-study.

Title:Multi-Objective Optimization Using Evolutionary Algorithms
Author: Kalyanmoy Deb
Publisher:John Wiley & Sons - 2001-07-05

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