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A New Hybrid Metaheuristic – Combining Stochastic Tunneling and Energy Landscape Paving

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Hybrid Metaheuristics (HM 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7919))

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Abstract

(Hybrid) metaheuristics such as simulated annealing, genetic algorithms, or extremal optimization play a most prominent role in global optimization. The performance of these algorithms and their respective sampling behavior during the search process are themselves interesting problems. Here, we show that a combination of two approaches – namely Energy Landscape Paving (ELP) and Stochastic Tunneling (STUN) – can overcome known problems of other Metropolis-sampling-based procedures. We show on grounds of non-equilibrium statistical mechanics and empirical evidence on the synergistic advantages of this combined approach and discuss simulations for a complex optimization problem.

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Authors and Affiliations

  1. Dept. of Computer Science, Dept. of Physics & Dept. of Biology, Technical University Darmstadt, Schnittspahnstr. 10, 64287, Darmstadt, Germany

    Kay Hamacher

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  1. Kay Hamacher
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Editor information

Editors and Affiliations

  1. Universitat Politècnica de Catalunya, Omega 213 Campus Nord, Jordi Girona 1-3, 08034, Barcelona, Spain

    María J. Blesa

  2. IKERBASQUE, Basque Foundation for Science, Department of Computer Science and Artificial Intelligence, University of the Basque Country, Paseo Manuel Lardizabal 1, 20018, San Sebastian, Spain

    Christian Blum

  3. Department of Mathematics and Applications “R. Caccioppoli”, Compl. M.S.A., University of Naples Federico II, Via Cintia, 80126, Naples, Italy

    Paola Festa

  4. DISI, Università di Bologna, Campus of Cesena, Via Venezia 52, 47521, Cesena, Italy

    Andrea Roli

  5. IRIDIA CP 194/6, Université Libre de Bruxelles, Avenue Franklin D. Roosevelt 50, 1050, Bruxelles, Belgium

    Michael Sampels

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Hamacher, K. (2013). A New Hybrid Metaheuristic – Combining Stochastic Tunneling and Energy Landscape Paving. In: Blesa, M.J., Blum, C., Festa, P., Roli, A., Sampels, M. (eds) Hybrid Metaheuristics. HM 2013. Lecture Notes in Computer Science, vol 7919. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38516-2_9

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  • DOI: https://doi.org/10.1007/978-3-642-38516-2_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38515-5

  • Online ISBN: 978-3-642-38516-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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