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DISH Solving the GNBG-generated Test Suite

Published: 01 August 2024 Publication History

Abstract

This paper presents an extended abstract describing an entry into the benchmarking competition on a new GNBG-generated Test Suite. We are presenting the results of our previously published Distance based parameter adaptation for Success-History based Differential Evolution (DISH) algorithm based on state of the art adaptive differential evolution variants. The key feature of our algorithm is a prolonged exploration due to an updated weighting scheme for control parameter adaptation. The results show that our contestant is able to locate the global optima on 12 out of the 24 test functions.

References

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Claus Aranha, Christian L Camacho Villalón, Felipe Campelo, Marco Dorigo. Rubén Ruiz, Marc Sevaux, Kenneth Sörensen, and Thomas Stützle. 2022. Metaphor-based metaheuristics, a call for action: the elephant in the room. Swarm Intelligence 16, 1 (2022), 1--6.
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Thomas Bartz-Beielstein, Carola Doerr, Daan van den Berg, Jakob Bossek, Sowmya Chandrasekaran, Tome Eftimov, Andreas Fischbach, Pascal Kerschke, William La Cava, Manuel Lopez-Ibanez, et al. 2020. Benchmarking in optimization: Best practice and open issues. arXiv preprint arXiv:2007.03488 (2020).
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Janez Brest, Mirjam Sepesy Maučec, and Borko Bošković. 2017. Single objective real-parameter optimization: Algorithm jSO. In 2017 IEEE congress on evolutionary computation (CEC). IEEE, 1311--1318.
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Ryoji Tanabe and Alex S Fukunaga. 2014. Improving the search performance of SHADE using linear population size reduction. In 2014 IEEE congress on evolutionary computation (CEC). IEEE, 1658--1665.
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Adam Viktorin, Roman Senkerik, Michal Pluhacek, Tomas Kadavy, and Ales Zamuda. 2019. Distance based parameter adaptation for success-history based differential evolution. Swarm and Evolutionary Computation 50 (2019), 100462.
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Danial Yazdani, Mohammad Nabi Omidvar, Delaram Yazdani, Kalyanmoy Deb, and Amir H. Gandomi. 2023. GNBG: A Generalized and Configurable Benchmark Generator for Continuous Numerical Optimization. arXiv:2312.07083 [cs.NE]

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Published In

cover image ACM Conferences
GECCO '24 Companion: Proceedings of the Genetic and Evolutionary Computation Conference Companion
July 2024
2187 pages
ISBN:9798400704956
DOI:10.1145/3638530
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s).

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Association for Computing Machinery

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Publication History

Published: 01 August 2024

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Author Tags

  1. evolutionary computation
  2. benchmarking

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  • Internal Grant Agency of the Tomas Bata University in Zlin

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GECCO '24 Companion
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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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