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An Adaptive Memetic Algorithm for Multi-robot Path-Planning

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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

This paper provides a novel approach to design an adaptive memetic algorithm by utilizing the composite benefits of Differential Evolution for global search and Q-learning for local refinement. The performance of the proposed adaptive memetic algorithm has been studied on a real-time multi-robot path-planning problem. Experimental results obtained for both simulation and real frameworks indicate that the proposed algorithm based path-planning scheme outperforms real coded Genetic Algorithm, Particle Swarm Optimization and Differential Evolution, particularly its currently best version with respect to two standard metrics defined in the literature.

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References

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Author information

Authors and Affiliations

  1. ETCE Depratment, Jadavpur University, India

    Pratyusha Rakshit, Dhrubojyoti Banerjee, Amit Konar & Ramadoss Janarthanan

Authors
  1. Pratyusha Rakshit
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  2. Dhrubojyoti Banerjee
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  3. Amit Konar
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  4. Ramadoss Janarthanan
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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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Rakshit, P., Banerjee, D., Konar, A., Janarthanan, R. (2012). An Adaptive Memetic Algorithm for Multi-robot Path-Planning. 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_30

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  • DOI: https://doi.org/10.1007/978-3-642-35380-2_30

  • 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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