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Configurable Intelligent Optimization Algorithm

Design and Practice in Manufacturing

  • Fei Tao
  • Lin Zhang
  • Yuanjun Laili

Part of the Springer Series in Advanced Manufacturing book series (SSAM)

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Introduction and Overview

    1. Front Matter
      Pages 1-2
    2. Fei Tao, Yuanjun Laili, Lin Zhang
      Pages 3-33
    3. Fei Tao, Yuanjun Laili, Lin Zhang
      Pages 35-80
  3. Design and Implementation

    1. Front Matter
      Pages 81-82
    2. Fei Tao, Yuanjun Laili, Lin Zhang
      Pages 83-105
    3. Fei Tao, Lin Zhang, Yuanjun Laili
      Pages 107-126
    4. Fei Tao, Lin Zhang, Yuanjun Laili
      Pages 127-154
  4. Application of Improved Intelligent Optimization Algorithms

    1. Front Matter
      Pages 155-155
    2. Fei Tao, Lin Zhang, Yuanjun Laili
      Pages 157-189
    3. Fei Tao, Lin Zhang, Yuanjun Laili
      Pages 191-224
  5. Application of Hybrid Intelligent Optimization Algorithms

    1. Front Matter
      Pages 225-225
    2. Fei Tao, Lin Zhang, Yuanjun Laili
      Pages 227-256
  6. Application of Parallel Intelligent Optimization Algorithms

    1. Front Matter
      Pages 289-289
    2. Yuanjun Laili, Fei Tao, Lin Zhang
      Pages 291-331
    3. Fei Tao, Lin Zhang, Yuanjun Laili
      Pages 333-347
  7. Future Works of Configurable Intelligent Optimization Algorithm

    1. Front Matter
      Pages 349-349
    2. Fei Tao, Lin Zhang, Yuanjun Laili
      Pages 351-361

About this book

Introduction

Presenting the concept and design and implementation of configurable intelligent optimization algorithms in manufacturing systems, this book provides a new configuration method to optimize manufacturing processes. It provides a comprehensive elaboration of basic intelligent optimization algorithms, and demonstrates how their improvement, hybridization and parallelization can be applied to manufacturing. Furthermore, various applications of these intelligent optimization algorithms are exemplified in detail, chapter by chapter. The intelligent optimization algorithm is not just a single algorithm; instead it is a general advanced optimization mechanism which is highly scalable with robustness and randomness. Therefore, this book demonstrates the flexibility of these algorithms, as well as their robustness and reusability in order to solve mass complicated problems in manufacturing.

Since the genetic algorithm was presented decades ago, a large number of intelligent optimization algorithms and their improvements have been developed. However, little work has been done to extend their applications and verify their competence in solving complicated problems in manufacturing.

This book will provide an invaluable resource to students, researchers, consultants and industry professionals interested in engineering optimization. It will also be particularly useful to three groups of readers: algorithm beginners, optimization engineers and senior algorithm designers. It offers a detailed description of intelligent optimization algorithms to algorithm beginners; recommends new configurable design methods for optimization engineers, and provides future trends and challenges of the new configuration mechanism to senior algorithm designers.

Keywords

Configuration Intelligent Optimization Algorithm Hybrid Intelligent Optimization Algorithm Manufacturing System Optimization and Scheduling Parallel Intelligent Optimization Algorithm

Authors and affiliations

  • Fei Tao
    • 1
  • Lin Zhang
    • 2
  • Yuanjun Laili
    • 3
  1. 1.School of Automation Science and Electrical EngineeringBeihang University (BUAA)BeijingChina
  2. 2.School of Automation Science and Electrical EngineeringBeihang University (BUAA)BeijingChina
  3. 3.School of Automation Science and Electrical EngineeringBeihang University (BUAA)BeijingChina

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-08840-2
  • Copyright Information Springer International Publishing Switzerland 2015
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-319-08839-6
  • Online ISBN 978-3-319-08840-2
  • Series Print ISSN 1860-5168
  • Series Online ISSN 2196-1735
  • Buy this book on publisher's site
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