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Glowworm Swarm Optimization for Multimodal Search Spaces

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Handbook of Swarm Intelligence

Part of the book series: Adaptation, Learning, and Optimization ((ALO,volume 8))

Summary

This chapter presents glowworm swarm optimization (GSO), a novel swarm intelligence algorithm, which was recently proposed for simultaneous capture of multiple optima of multimodal functions. In particular, GSO prescribes individual-level rules that cause a swarm of agents deployed in a signal medium to automatically partition into subswarms that converge on the multiple sources of the signal profile. The sources could represent multiple optima in a numerical optimization problem or physical quantities like sound, light, or heat in a realistic robotic source localization task. We present the basic GSO model and use a numerical example to characterize the group-level phases of the algorithm that gives an insight into how GSO explicitly addresses the issue of achievement/maintenance of swarm diversity. We briefly summarize the results from the application of GSO to the following three problems−multimodal function optimization, signal source localization, and pursuit of mobile signal sources.

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Author information

Authors and Affiliations

  1. Department of Computer Science, University of Vermont, Burlington, VT, USA

    K. N. Krishnanand

  2. Guidance, Control and Decision Systems Laboratoty (GCDSL), Department of Aerospace Engineering, Indian Institute of Science, Bangalore, India

    D. Ghose

Authors
  1. K. N. Krishnanand
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  2. D. Ghose
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Editor information

Editors and Affiliations

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

    Bijaya Ketan Panigrahi

  2. Director of Research and Postgraduate Office, Xi’an Jiaotong-Liverpool University , 215123, Suzhou, China

    Yuhui Shi

  3. School of Electrical & Electronic Engineering, Nanyang Technological University , 639798, Singapore

    Meng-Hiot Lim

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© 2011 Springer-Verlag Berlin Heidelberg

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Krishnanand, K.N., Ghose, D. (2011). Glowworm Swarm Optimization for Multimodal Search Spaces. In: Panigrahi, B.K., Shi, Y., Lim, MH. (eds) Handbook of Swarm Intelligence. Adaptation, Learning, and Optimization, vol 8. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17390-5_19

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  • DOI: https://doi.org/10.1007/978-3-642-17390-5_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17389-9

  • Online ISBN: 978-3-642-17390-5

  • eBook Packages: EngineeringEngineering (R0)

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