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Differential Evolution with a Relational Neighbourhood-Based Strategy for Numerical Optimization

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Swarm, Evolutionary, and Memetic Computing (SEMCCO 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7677))

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Abstract

Differential Evolution is a competitive optimizer, with a simplified framework, for numerical optimization problems. Many research works have been done to enhance the performance of Differential Evolution by developing the evolutionary operators. One of the major challenges in DE is performing intelligent search based on population topology. To maintain the diversity in the population as well as to improve the convergence rate, we have introduced a mutation strategy based on relative mapping of the members in population topology. Also Gamma and Cauchy distribution have been adapted in the control parameter framework to include randomness and thorough search. The proposed DE framework is referred to as the Relational Neighbourhood Differential Evolution (ReNbd-DE) and its performance is reported on the set of CEC2005 benchmark functions.

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Authors and Affiliations

  1. Dept. of Electronics and Communication Engineering, Jadavpur University, Kolkata, 700 032, India

    Souvik Kundu, Digbalay Bose & Subhodip Biswas

Authors
  1. Souvik Kundu
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  2. Digbalay Bose
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  3. Subhodip Biswas
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Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, Indian Institute of Technology, 110016, Delhi, India

    Bijaya Ketan Panigrahi

  2. Electronics and Communication Sciences Unit, Indian Statistical Institute, 700108, Kolkata, India

    Swagatam Das

  3. School of Electrical and Electronic Engineering, Nanyang Technological University, Block N4, 2b-39, Nanyang Avenue, 639798, Singapore, Singapore

    Ponnuthurai Nagaratnam Suganthan

  4. Department of Electronics and Telecom. Engineering, Institute of Technical Education & Research, Siksha ’O’ Anusandhan University, 751030, Bhubaneswar, Odisha, India

    Pradipta Kumar Nanda

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© 2012 Springer-Verlag Berlin Heidelberg

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Kundu, S., Bose, D., Biswas, S. (2012). Differential Evolution with a Relational Neighbourhood-Based Strategy for Numerical Optimization. In: Panigrahi, B.K., Das, S., Suganthan, P.N., Nanda, P.K. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2012. Lecture Notes in Computer Science, vol 7677. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35380-2_23

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  • DOI: https://doi.org/10.1007/978-3-642-35380-2_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35379-6

  • Online ISBN: 978-3-642-35380-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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