Network-based Distributed Planning Using Coevolutionary Algorithms
eBook - PDF

Network-based Distributed Planning Using Coevolutionary Algorithms

  1. 192 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Network-based Distributed Planning Using Coevolutionary Algorithms

About this book

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 distributed evolutionary agents and mobile agents.The methodology discussed in this book can have a fundamental impact on the principles and practice of engineering in the distributed, network-based environment that is emerging within and among corporate enterprise systems. In addition, the conceptual framework of the approach to distributed decision systems described may have much wider implications for network-based systems and applications.

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Yes, you can access Network-based Distributed Planning Using Coevolutionary Algorithms by Arthur C Sanderson, Raj Subbu in PDF and/or ePUB format, as well as other popular books in Biological Sciences & Science General. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Contents
  2. Foreword
  3. Preface
  4. 1. Introduction
  5. 2. Background and Related Work
  6. 3. Problem Formulation and Analysis
  7. 4. Theory and Analysis of Evolutionary Optimization
  8. 5. Theory and Analysis of Distributed Coevolutionary Optimization
  9. 6. Performance Evaluation Based on Ideal Objectives
  10. 7. Coevolutionary Virtual Design Environment
  11. 8. Evaluation and Analysis
  12. 9. Conclusions
  13. Appendix A Evolutionary Algorithm Theory
  14. Appendix B Models for the Printed Circuit Assembly Problem
  15. Bibliography
  16. Index