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 Author: | |
|---|---|
| Other Authors: | |
| Format: | Electronic eBook |
| Language: | English |
| Published: |
River Edge, NJ :
World Scientific,
2004.
|
| Series: | Series in intelligent control and intelligent automation ;
v. 13. |
| Subjects: | |
| Online Access: | DE-862 DE-863 |
| 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 distr. |
| Item Description: | Based on doctoral research, 1996-2000--Rensselaer Polytechnic Institute. |
| Physical Description: | 1 online resource (xix, 172 pages) : illustrations |
| Bibliography: | Includes bibliographical references (pages 159-168) and index. |
| ISBN: | 9789812794857 9812794859 |
Staff View
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| 505 | 0 | |a 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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| 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 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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| indexdate | 2025-04-11T08:36:13Z |
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| series | Series in intelligent control and intelligent automation ; |
| series2 | Series in intelligent control and intelligent automation ; |
| spelling | Subbu, Raj. Network-based distributed planning using coevolutionary algorithms / Raj Subbu, Arthur C Sanderson. River Edge, NJ : World Scientific, 2004. 1 online resource (xix, 172 pages) : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier data file Series in intelligent control and intelligent automation ; v. 13 Includes bibliographical references (pages 159-168) and index. Based on doctoral research, 1996-2000--Rensselaer Polytechnic Institute. Print version record. 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. 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. Electronic data processing Distributed processing. http://id.loc.gov/authorities/subjects/sh85042293 Algorithms. http://id.loc.gov/authorities/subjects/sh85003487 Intelligent agents (Computer software) http://id.loc.gov/authorities/subjects/sh97000493 Algorithms https://id.nlm.nih.gov/mesh/D000465 Traitement réparti. Algorithmes. Agents intelligents (Logiciels) algorithms. aat REFERENCE General. bisacsh Algorithms fast Electronic data processing Distributed processing fast Intelligent agents (Computer software) fast Sanderson, A. C. (Arthur C.) http://id.loc.gov/authorities/names/n90609391 Print version: Subbu, Raj. Network-based distributed planning using coevolutionary algorithms. River Edge, NJ : World Scientific, 2004 9812387544 9789812387547 (DLC) 2004274894 (OCoLC)55635641 Series in intelligent control and intelligent automation ; v. 13. http://id.loc.gov/authorities/names/n95071459 |
| spellingShingle | Subbu, Raj Network-based distributed planning using coevolutionary algorithms / Series in intelligent control and intelligent automation ; 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. Electronic data processing Distributed processing. http://id.loc.gov/authorities/subjects/sh85042293 Algorithms. http://id.loc.gov/authorities/subjects/sh85003487 Intelligent agents (Computer software) http://id.loc.gov/authorities/subjects/sh97000493 Algorithms https://id.nlm.nih.gov/mesh/D000465 Traitement réparti. Algorithmes. Agents intelligents (Logiciels) algorithms. aat REFERENCE General. bisacsh Algorithms fast Electronic data processing Distributed processing fast Intelligent agents (Computer software) fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh85042293 http://id.loc.gov/authorities/subjects/sh85003487 http://id.loc.gov/authorities/subjects/sh97000493 https://id.nlm.nih.gov/mesh/D000465 |
| title | Network-based distributed planning using coevolutionary algorithms / |
| title_auth | Network-based distributed planning using coevolutionary algorithms / |
| title_exact_search | Network-based distributed planning using coevolutionary algorithms / |
| title_full | Network-based distributed planning using coevolutionary algorithms / Raj Subbu, Arthur C Sanderson. |
| title_fullStr | Network-based distributed planning using coevolutionary algorithms / Raj Subbu, Arthur C Sanderson. |
| title_full_unstemmed | Network-based distributed planning using coevolutionary algorithms / Raj Subbu, Arthur C Sanderson. |
| title_short | Network-based distributed planning using coevolutionary algorithms / |
| title_sort | network based distributed planning using coevolutionary algorithms |
| topic | Electronic data processing Distributed processing. http://id.loc.gov/authorities/subjects/sh85042293 Algorithms. http://id.loc.gov/authorities/subjects/sh85003487 Intelligent agents (Computer software) http://id.loc.gov/authorities/subjects/sh97000493 Algorithms https://id.nlm.nih.gov/mesh/D000465 Traitement réparti. Algorithmes. Agents intelligents (Logiciels) algorithms. aat REFERENCE General. bisacsh Algorithms fast Electronic data processing Distributed processing fast Intelligent agents (Computer software) fast |
| topic_facet | Electronic data processing Distributed processing. Algorithms. Intelligent agents (Computer software) Algorithms Traitement réparti. Algorithmes. Agents intelligents (Logiciels) algorithms. REFERENCE General. Electronic data processing Distributed processing |
| work_keys_str_mv | AT subburaj networkbaseddistributedplanningusingcoevolutionaryalgorithms AT sandersonac networkbaseddistributedplanningusingcoevolutionaryalgorithms |