Multi Objective Optimization

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Multi-Objective Optimization in Computational Intelligence: Theory and Practice

Multi-Objective Optimization in Computational Intelligence: Theory and Practice
Author :
Publisher : IGI Global
Total Pages : 495
Release :
ISBN-10 : 9781599045009
ISBN-13 : 1599045001
Rating : 4/5 (001 Downloads)

Book Synopsis Multi-Objective Optimization in Computational Intelligence: Theory and Practice by : Thu Bui, Lam

Download or read book Multi-Objective Optimization in Computational Intelligence: Theory and Practice written by Thu Bui, Lam and published by IGI Global. This book was released on 2008-05-31 with total page 495 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multi-objective optimization (MO) is a fast-developing field in computational intelligence research. Giving decision makers more options to choose from using some post-analysis preference information, there are a number of competitive MO techniques with an increasingly large number of MO real-world applications. Multi-Objective Optimization in Computational Intelligence: Theory and Practice explores the theoretical, as well as empirical, performance of MOs on a wide range of optimization issues including combinatorial, real-valued, dynamic, and noisy problems. This book provides scholars, academics, and practitioners with a fundamental, comprehensive collection of research on multi-objective optimization techniques, applications, and practices.


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Multi-Objective Optimization in Computational Intelligence: Theory and Practice
Language: en
Pages: 495
Authors: Thu Bui, Lam
Categories: Technology & Engineering
Type: BOOK - Published: 2008-05-31 - Publisher: IGI Global

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Multi-objective optimization (MO) is a fast-developing field in computational intelligence research. Giving decision makers more options to choose from using so
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This text offers many multiobjective optimization methods accompanied by analytical examples, and it treats problems not only in engineering but also operations
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This book focuses on the most well-regarded and recent nature-inspired algorithms capable of solving optimization problems with multiple objectives. Firstly, it