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A new mutation operator with the ability to adjust exploration and exploitation for DE algorithm

Published:13 July 2019Publication History

ABSTRACT

This paper proposes a new mutation operator Current --- to --- better-AC with an angle control rule for DE algorithm. This new mutation operator has the potential to automatically adjust the exploration and exploitation based on the angle control rule. Under the control of this rule, the individuals pair for generating mutation vector is tendentiously selected. In Current --- to --- better-AC, only high-ranking individuals are permitted to use the angle control rule, while low-ranking individuals are encouraged to move to a random high-ranking individual. This method is embedded into JADE as a new algorithm AC-JADE, and its performance is tested by COCO benchmarks. Experimental results show that AC-JADE performs better than JADE.

References

  1. Anne Auger, Steffen Finck, Nikolaus Hansen, and Raymond Ros. 2010. BBOB 2010: Comparison tables of all algorithms on all noiseless functions. Ph.D. Dissertation. INRIA.Google ScholarGoogle Scholar
  2. Anne Auger, Nikolaus Hansen, and Marc Schoenauer. 2012. Benchmarking of continuous black box optimization algorithms. (2012).Google ScholarGoogle Scholar
  3. Nikolaus Hansen, Anne Auger, Olaf Mersmann, Tea Tusar, and Dimo Brockhoff. 2016. COCO: A platform for comparing continuous optimizers in a black-box setting. arXiv preprint arXiv:1603.08785 (2016).Google ScholarGoogle Scholar
  4. Petr Pošík and Václav Klemš. 2012. Benchmarking the differential evolution with adaptive encoding on noiseless functions. In Proceedings of the 14th annual conference companion on Genetic and evolutionary computation. ACM, 189--196. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Jingqiao Zhang and Arthur C Sanderson. 2009. JADE: adaptive differential evolution with optional external archive. IEEE Transactions on evolutionary computation 13, 5 (2009), 945--958. Google ScholarGoogle ScholarDigital LibraryDigital Library

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  1. A new mutation operator with the ability to adjust exploration and exploitation for DE algorithm

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    • Published in

      cover image ACM Conferences
      GECCO '19: Proceedings of the Genetic and Evolutionary Computation Conference Companion
      July 2019
      2161 pages
      ISBN:9781450367486
      DOI:10.1145/3319619

      Copyright © 2019 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 13 July 2019

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      Overall Acceptance Rate1,669of4,410submissions,38%

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