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Experimental Study on Bound Handling Techniques for Multi-objective Particle Swarm Optimization

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Innovations in Bio-Inspired Computing and Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 424))

Abstract

Many real world optimization scenarios impose certain limitations, in terms of constraints and bounds, on various factors affecting the problem. In this paper we formulate several methods for bound handling of decision variables involved in solving a multi-objective optimization problem using particle swarm optimization algorithm. We further compare the performance of these methods on different 2-objective test problems.

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Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, Indian Institute of Technology Guwahati, Guwahati, 781039, Assam, India

    Devang Agarwal & Deepak Sharma

Authors
  1. Devang Agarwal
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  2. Deepak Sharma
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Corresponding authors

Correspondence to Devang Agarwal or Deepak Sharma .

Editor information

Editors and Affiliations

  1. Dep. of Computer Science, VŠB – Technical Univ. of Ostrava, Ostrava, Czech Republic

    Václav Snášel

  2. (MIR Labs), Scientific Net Innov & Res Excel, Auburn, Washington, USA

    Ajit Abraham

  3. Faculty of Elec. Eng. & Comp. Sci., VÅ B - Technical University of Ostrava, Ostrava-Poruba, Czech Republic

    Pavel Krömer

  4. Department of Paper Technology, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Millie Pant

  5. Fac of Info & Comm, Comp Inte & Tech Lab, Universiti Teknikal Malaysia Melaka, Durian Tunggal, Malaysia

    Azah Kamilah Muda

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Agarwal, D., Sharma, D. (2016). Experimental Study on Bound Handling Techniques for Multi-objective Particle Swarm Optimization. In: Snášel, V., Abraham, A., Krömer, P., Pant, M., Muda, A. (eds) Innovations in Bio-Inspired Computing and Applications. Advances in Intelligent Systems and Computing, vol 424. Springer, Cham. https://doi.org/10.1007/978-3-319-28031-8_49

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  • DOI: https://doi.org/10.1007/978-3-319-28031-8_49

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-28030-1

  • Online ISBN: 978-3-319-28031-8

  • eBook Packages: EngineeringEngineering (R0)

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