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POPMUSIC

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Abstract

This chapter presents POPMUSIC, a general decomposition-based framework within the realm of metaheuristics and matheuristics that has been successfully applied to various combinatorial optimization problems. POPMUSIC is especially useful for designing heuristic methods for large combinatorial problems that can be partially optimized. The basic idea is to optimize subparts of solutions until a local optimum is reached. Implementations of the technique to various problems show its broad applicability and efficiency for tackling especially large-size instances.

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Author information

Authors and Affiliations

  1. Embedded Information Systems, HEIG-VD, University of Applied Sciences and Arts of Western Switzerland, Yverdon-les-Bains, Delémont, Switzerland

    Éric D. Taillard

  2. Faculty of Business Administration, Institute of Information Systems, University of Hamburg, Hamburg, Germany

    Stefan Voß

Authors
  1. Éric D. Taillard
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  2. Stefan Voß
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Corresponding author

Correspondence to Éric D. Taillard .

Editor information

Editors and Affiliations

  1. Statistics and Operations Research Department, University of Valencia, Valencia, Spain

    Rafael Martí

  2. Department of Industrial and Systems Engineering, University of Florida, Gainesville, Florida, USA

    Panos M. Pardalos

  3. Amazon.com, Inc. and University of Washington, Seattle, Washington, USA

    Mauricio G. C. Resende

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Taillard, É.D., Voß, S. (2018). POPMUSIC. In: Martí, R., Pardalos, P., Resende, M. (eds) Handbook of Heuristics. Springer, Cham. https://doi.org/10.1007/978-3-319-07124-4_31

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