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Multi-objective Swarm Intelligence

Theoretical Advances and Applications

  • Book
  • © 2015

Overview

Editors:
  1. Satchidananda Dehuri

    1. Department of Information and Communication Technology, Fakir Mohan University, Balasore, India

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  2. Alok Kumar Jagadev

    1. Department of Computer Science and Engineering, Siksha 'O' Anusandhan University, Bhubaneswar, India

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  3. Mrutyunjaya Panda

    1. Gandhi Institute for Technological Advancement, Bhubaneswar, India

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  • Recent research on Multi objective Swarm Intelligence
  • Presents theoretical advances and applications
  • Written by leading experts in the field
  • Includes supplementary material: sn.pub/extras

Part of the book series: Studies in Computational Intelligence (SCI, volume 592)

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Table of contents (7 chapters)

  1. Front Matter

    Pages i-xiv
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  2. A Comprehensive Review on Bacteria Foraging Optimization Technique

    • B. Selva Rani, Ch. Aswani Kumar
    Pages 1-25

  3. Swarm Intelligence in Multiple and Many Objectives Optimization: A Survey and Topical Study on EEG Signal Analysis

    • B. S. P. Mishra, Satchidanand Dehuri, Sung-Bae Cho
    Pages 27-73

  4. Comparison of Various Approaches in Multi-objective Particle Swarm Optimization (MOPSO): Empirical Study

    • Swagatika Devi, Alok Kumar Jagadev, Sachidananda Dehuri
    Pages 75-103

  5. Binary Ant Colony Optimization for Subset Problems

    • Nadia Abd-Alsabour
    Pages 105-121

  6. Ant Colony for Locality Foraging in Image Enhancement

    • Gabriele Simone, Davide Gadia, Ivar Farup, Alessandro Rizzi
    Pages 123-142

  7. Uncertainty Based Hybrid Particle Swarm Optimization Techniques and Their Applications

    • J. Anuradha, B. K. Tripathy
    Pages 143-169

  8. Hybridization of Evolutionary and Swarm Intelligence Techniques for Job Scheduling Problem

    • R. Uma Rani
    Pages 171-201
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Keywords

About this book

The aim of this book is to understand the state-of-the-art theoretical and practical advances of swarm intelligence. It comprises seven contemporary relevant chapters. In chapter 1, a review of Bacteria Foraging Optimization (BFO) techniques for both single and multiple criterions problem is presented. A survey on swarm intelligence for multiple and many objectives optimization is presented in chapter 2 along with a topical study on EEG signal analysis. Without compromising the extensive simulation study, a comparative study of variants of MOPSO is provided in chapter 3. Intractable problems like subset and job scheduling problems are discussed in chapters 4 and 7 by different hybrid swarm intelligence techniques. An attempt to study image enhancement by ant colony optimization is made in chapter 5. Finally, chapter 7 covers the aspect of uncertainty in data by hybrid PSO.       

Editors and Affiliations

  • Department of Information and Communication Technology, Fakir Mohan University, Balasore, India

    Satchidananda Dehuri

  • Department of Computer Science and Engineering, Siksha 'O' Anusandhan University, Bhubaneswar, India

    Alok Kumar Jagadev

  • Gandhi Institute for Technological Advancement, Bhubaneswar, India

    Mrutyunjaya Panda

Bibliographic Information

  • Book Title: Multi-objective Swarm Intelligence

  • Book Subtitle: Theoretical Advances and Applications

  • Editors: Satchidananda Dehuri, Alok Kumar Jagadev, Mrutyunjaya Panda

  • Series Title: Studies in Computational Intelligence

  • DOI: https://doi.org/10.1007/978-3-662-46309-3

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Engineering, Engineering (R0)

  • Copyright Information: Springer-Verlag Berlin Heidelberg 2015

  • Hardcover ISBN: 978-3-662-46308-6Published: 26 March 2015

  • Softcover ISBN: 978-3-662-52365-0Published: 09 October 2016

  • eBook ISBN: 978-3-662-46309-3Published: 10 March 2015

  • Series ISSN: 1860-949X

  • Series E-ISSN: 1860-9503

  • Edition Number: 1

  • Number of Pages: XIV, 201

  • Number of Illustrations: 49 b/w illustrations, 11 illustrations in colour

  • Topics: Computational Intelligence, Artificial Intelligence

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