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Nature Inspired Cooperative Strategies for Optimization (NICSO 2011) pp 41–55Cite as

An Adaptive Multiagent Strategy for Solving Combinatorial Dynamic Optimization Problems

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 387))

Abstract

This work presents the results obtained when using a decentralised multiagent strategy (Agents) to solve dynamic optimization problems of a combinatorial nature. To improve the results of the strategy, we also include a simple adaptive scheme for several configuration variants of a mutation operator in order to obtain a more robust behaviour. The adaptive scheme is also tested on an evolutionary algorithm (EA). Finally, both Agents and EA are compared against the recent state of the art adaptive hill-climbing memetic algorithm (AHMA).

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Author information

Authors and Affiliations

  1. DECSAI, ETSIIT, CITIC-UGR, University of Granada, C/Daniel Saucedo Aranda, s/n, E-18071, Granada, Spain

    Juan R. González, Carlos Cruz, Ignacio G. del Amo & David A. Pelta

Authors
  1. Juan R. González
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  2. Carlos Cruz
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  3. Ignacio G. del Amo
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  4. David A. Pelta
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Editor information

Editors and Affiliations

  1. Dept. of Computer Science and A.I.E.T.S. Ingenieria Informatica y de Telecomunicación, University of Granada, C/ Periodista Daniel Saucedo Aranda s/n,, 18071, Granada, Spain

    David Alejandro Pelta

  2. School of Computer Science, University of Nottingham, Jubilee Campus Wollaton Road, NG8 1BB, Nottingham, UK

    Natalio Krasnogor

  3. Center for Cognitive and Neural Studies, Babes-Bolyai University of Cluj Napoca, (Coneural), Str. Ciresilor 29, 400487, Cluj-Napoca, Romania

    Dan Dumitrescu

  4. Department of Computer Science, Babes-Bolyai University, Kogalniceanu 1, 400084, Cluj-Napoca, Romania

    Camelia Chira

  5. Faculty of Economics and Business Administration, Babes-Bolyai University of Cluj Napoca, Str. Teodor Mihali Nr. 58-60, 400591, Cluj Napoca, Romania

    Rodica Lung

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González, J.R., Cruz, C., del Amo, I.G., Pelta, D.A. (2011). An Adaptive Multiagent Strategy for Solving Combinatorial Dynamic Optimization Problems. In: Pelta, D.A., Krasnogor, N., Dumitrescu, D., Chira, C., Lung, R. (eds) Nature Inspired Cooperative Strategies for Optimization (NICSO 2011). Studies in Computational Intelligence, vol 387. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24094-2_3

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  • DOI: https://doi.org/10.1007/978-3-642-24094-2_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24093-5

  • Online ISBN: 978-3-642-24094-2

  • eBook Packages: EngineeringEngineering (R0)

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