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A critical analysis of the harmony search algorithm—How not to solve sudoku

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  • Weyland, Dennis

Abstract

This article presents a critical analysis of the harmony search metaheuristic framework. We formally prove that the harmony search algorithm is a special case of evolution strategies. First, this implies that the harmony search algorithm itself does not offer any novelty, apart from using a different terminology. Second, the performance of the best harmony search algorithm is always bounded by the performance that can be obtained by evolution strategies. Additionally, more than a decade of research about harmony search has not revealed any other sort of novelty or has led to any new insights or significant contributions in the field of heuristics. In short, there is no reason for harmony search to exist as a separate metaheuristic framework.

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  • Weyland, Dennis, 2015. "A critical analysis of the harmony search algorithm—How not to solve sudoku," Operations Research Perspectives, Elsevier, vol. 2(C), pages 97-105.
    • Handle: RePEc:eee:oprepe:v:2:y:2015:i:c:p:97-105
    DOI: 10.1016/j.orp.2015.04.001
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    References listed on IDEAS

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    1. Zong Woo Geem, 2010. "Research Commentary: Survival of the Fittest Algorithm or the Novelest Algorithm?," International Journal of Applied Metaheuristic Computing (IJAMC), IGI Global, vol. 1(4), pages 75-79, October.
    2. Dennis Weyland, 2010. "A Rigorous Analysis of the Harmony Search Algorithm: How the Research Community can be Misled by a “Novel” Methodology," International Journal of Applied Metaheuristic Computing (IJAMC), IGI Global, vol. 1(2), pages 50-60, April.
    3. Miriam Padberg, 2012. "Harmony Search Algorithms for binary optimization problems," Operations Research Proceedings, in: Diethard Klatte & Hans-Jakob Lüthi & Karl Schmedders (ed.), Operations Research Proceedings 2011, edition 127, pages 343-348, Springer.
    4. De Corte, Annelies & Sörensen, Kenneth, 2013. "Optimisation of gravity-fed water distribution network design: A critical review," European Journal of Operational Research, Elsevier, vol. 228(1), pages 1-10.
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    Cited by:

    1. Schmidt, Mischa & Åhlund, Christer, 2018. "Smart buildings as Cyber-Physical Systems: Data-driven predictive control strategies for energy efficiency," Renewable and Sustainable Energy Reviews, Elsevier, vol. 90(C), pages 742-756.
    2. Deeam Najmadeen Hama Rashid & Tarik A. Rashid & Seyedali Mirjalili, 2021. "ANA: Ant Nesting Algorithm for Optimizing Real-World Problems," Mathematics, MDPI, vol. 9(23), pages 1-30, December.
    3. Assif Assad & Kusum Deep, 2018. "Harmony search based memetic algorithms for solving sudoku," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 9(4), pages 741-754, August.
    4. Jann Michael Weinand & Kenneth Sorensen & Pablo San Segundo & Max Kleinebrahm & Russell McKenna, 2020. "Research trends in combinatorial optimisation," Papers 2012.01294, arXiv.org.

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