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Evolutionary Computation for Dynamic Optimization Problems

  • Conference proceedings
  • © 2013

Overview

Editors:
  1. Shengxiang Yang

    1. , School of Computer Science and Informati, De Montfort University, Leicester, United Kingdom

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    You can also search for this editor in PubMed   Google Scholar

  2. Xin Yao

    1. , School of Computer Science, University of Birmingham, Birmingham, United Kingdom

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  • Compilation on the state-of-the-art of evolutionary computation for dynamic optimization problems
  • Valuable reference book for the domain of Evolutionary Computation for Dynamic Optimization Problems in particular and Computational Intelligence in general
  • Written by leading experts in the field

Part of the book series: Studies in Computational Intelligence (SCI, volume 490)

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Table of contents (17 papers)

  1. Front Matter

    Pages 1-24
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  2. Fundamentals

    1. Front Matter

      Pages 1-1
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    2. Evolutionary Dynamic Optimization: Test and Evaluation Environments

      • Shengxiang Yang, Trung Thanh Nguyen, Changhe Li
      Pages 3-37

    3. Evolutionary Dynamic Optimization: Methodologies

      • Trung Thanh Nguyen, Shengxiang Yang, Juergen Branke, Xin Yao
      Pages 39-64

    4. Evolutionary Dynamic Optimization: Challenges and Perspectives

      • Philipp Rohlfshagen, Xin Yao
      Pages 65-84

    5. Dynamic Multi-objective Optimization: A Survey of the State-of-the-Art

      • Carlo Raquel, Xin Yao
      Pages 85-106

  3. Algorithm Design

    1. Front Matter

      Pages 107-107
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    2. A Comparative Study on Particle Swarm Optimization in Dynamic Environments

      • Changhe Li, Shengxiang Yang
      Pages 109-136

    3. Memetic Algorithms for Dynamic Optimization Problems

      • Hongfeng Wang, Shengxiang Yang
      Pages 137-170

    4. BIPOP: A New Algorithm with Explicit Exploration/Exploitation Control for Dynamic Optimization Problems

      • Enrique Alba, Hajer Ben-Romdhane, Saoussen Krichen, Briseida Sarasola
      Pages 171-191

    5. Evolutionary Optimization on Continuous Dynamic Constrained Problems - An Analysis

      • Trung Thanh Nguyen, Xin Yao
      Pages 193-217

  4. Theoretical Analysis

    1. Front Matter

      Pages 219-219
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    2. Theoretical Advances in Evolutionary Dynamic Optimization

      • Philipp Rohlfshagen, Per Kristian Lehre, Xin Yao
      Pages 221-240

    3. Analyzing Evolutionary Algorithms for Dynamic Optimization Problems Based on the Dynamical Systems Approach

      • Renato Tinós, Shengxiang Yang
      Pages 241-267

    4. Dynamic Fitness Landscape Analysis

      • Hendrik Richter
      Pages 269-297

    5. Dynamics in the Multi-objective Subset Sum: Analysing the Behavior of Population Based Algorithms

      • Iulia Maria Comsa, Crina Grosan, Shengxiang Yang
      Pages 299-313

  5. Applications

    1. Front Matter

      Pages 315-315
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    2. Ant Colony Optimization Algorithms with Immigrants Schemes for the Dynamic Travelling Salesman Problem

      • Michalis Mavrovouniotis, Shengxiang Yang
      Pages 317-341

    3. Genetic Algorithms for Dynamic Routing Problems in Mobile Ad Hoc Networks

      • Hui Cheng, Shengxiang Yang
      Pages 343-375

    4. Evolutionary Computation for Dynamic Capacitated Arc Routing Problem

      • Yi Mei, Ke Tang, Xin Yao
      Pages 377-401
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Keywords

About this book

This book provides a compilation on the state-of-the-art and recent advances of evolutionary computation for dynamic optimization problems. The motivation for this book arises from the fact that many real-world optimization problems and engineering systems are subject to dynamic environments, where changes occur over time.

Key issues for addressing dynamic optimization problems in evolutionary computation, including fundamentals, algorithm design, theoretical analysis, and real-world applications, are presented. "Evolutionary Computation for Dynamic Optimization Problems" is a valuable reference to scientists, researchers, professionals and students in the field of engineering and science, particularly in the areas of computational intelligence, nature- and bio-inspired computing, and evolutionary computation.

Editors and Affiliations

  • , School of Computer Science and Informati, De Montfort University, Leicester, United Kingdom

    Shengxiang Yang

  • , School of Computer Science, University of Birmingham, Birmingham, United Kingdom

    Xin Yao

Bibliographic Information

  • Book Title: Evolutionary Computation for Dynamic Optimization Problems

  • Editors: Shengxiang Yang, Xin Yao

  • Series Title: Studies in Computational Intelligence

  • DOI: https://doi.org/10.1007/978-3-642-38416-5

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer-Verlag Berlin Heidelberg 2013

  • Hardcover ISBN: 978-3-642-38415-8Published: 28 May 2013

  • Softcover ISBN: 978-3-642-44843-0Published: 20 June 2015

  • eBook ISBN: 978-3-642-38416-5Published: 18 November 2013

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: XXVIII, 470

  • Topics: Computational Intelligence, Artificial Intelligence

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