| Document Type
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BL
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| Record Number
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1036251
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| Doc. No
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b790621
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| Main Entry
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Subbu, Raj.
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| Title & Author
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Network-based distributed planning using coevolutionary algorithms /\ Raj Subbu, Arthur C Sanderson.
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| Publication Statement
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River Edge, NJ :: World Scientific,, 2004.
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| Series Statement
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Series in intelligent control and intelligent automation ;; v. 13
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| Page. NO
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1 online resource (xix, 172 pages) :: illustrations
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| ISBN
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9789812794857
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: 9812794859
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9789812387547
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9812387544
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| Notes
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Based on doctoral research, 1996-2000--Rensselaer Polytechnic Institute.
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| Bibliographies/Indexes
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Includes bibliographical references (pages 159-168) and index.
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| Contents
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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 analysis of distributed coevolutionary optimization. 5.1. Introduction. 5.2. Theory. 5.3. Computational delay analysis -- 6. Performance evaluation based on ideal objectives. 6.1. Introduction. 6.2. Gaussian objectives. 6.3. Planar tile layout problems. 6.4. Design-supplier-manufacturing problem -- 7. Coevolutionary virtual design environment. 7.1. Introduction. 7.2. Application domain. 7.3. Evolutionary optimization. 7.4. Simulation environments -- 8. Evaluation and analysis. 8.1. Introduction. 8.2. Nature and evolution of planning decisions. 8.3. Strategy for performance evaluation. 8.4. Performance evaluation. 8.5. Applicability analysis of the frameworks -- 9. Conclusions. 9.1. Summary. 9.2. Future work.
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| Abstract
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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 distr.
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Algorithms
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Electronic data processing-- Distributed processing
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Intelligent agents (Computer software)
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Algorithms.
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Electronic data processing-- Distributed processing.
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Intelligent agents (Computer software)
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REFERENCE-- General.
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| Dewey Classification
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005.2/76
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| LC Classification
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QA76.9.D5S82 2004eb
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| Added Entry
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Sanderson, A. C., (Arthur C.)
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