Network-based distributed planning using coevolutionary algorithms /
In this book, efficient and scalable coevolutionary algorithms for distributed, network-based decision-making, which utilize objective functions are developed in a networked environment where internode communications are a primary factor in system performance. A theoretical foundation for this class...
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Main Authors: | |
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Corporate Authors: | |
Group Author: | |
Published: |
World Scientific Pub. Co.,
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Publisher Address: | Singapore ; River Edge, N.J. : |
Publication Dates: | 2004. |
Literature type: | eBook |
Language: | English |
Series: |
Series in intelligent control and intelligent automation ;
v. 13 |
Subjects: | |
Online Access: |
http://www.worldscientific.com/worldscibooks/10.1142/5470#t=toc |
Summary: |
In this book, efficient and scalable coevolutionary algorithms for distributed, network-based decision-making, which utilize objective functions are developed in a networked environment where internode communications are a primary factor in system performance. A theoretical foundation for this class of coevolutionary algorithms is introduced using techniques from stochastic process theory and mathematical analysis. A case study in distributed, network-based decision-making presents an implementation and detailed evaluation of the coevolutionary decision-making framework that incorporates dis |
Carrier Form: | 1 online resource (xix,172pages) : illustrations. |
Bibliography: | Includes bibliographical references (pages 159-168) and index. |
ISBN: | 9789812794857 (electronic bk.) |
CLC: | TP393 |
Contents: | 1. Introduction. 1.1. Motivation. 1.2. Approach. 1.3. Principal contributions. 1.4. Book outline -- 2. Background and related work. 2.1. Collaborative manufacturing. 2.2. Combinatorial optimization. 2.3. Evolutionary algorithms. 2.4. Agents. 2.5. Distributed problem solving -- 3. Problem formulation and analysis. 3.1. Introduction. 3.2. General problem formulation. 3.3. Printed circuit assembly problem. 3.4. Algorithm applicability analysis -- 4. Theory and analysis of evolutionary optimization. 4.1. Introduction. 4.2. Theoretical foundation. 4.3. Convergence analysis -- 5. Theory and analys |