Abstract
This article describes a new genetic-programming-based optimization method using a multi-gene approach along with a niching strategy and periodic domain constraints. The method is referred to as Niching MG-PMA, where MG refers to multi-gene and PMA to parameter mapping approach. Although it was designed to be a multimodal optimization method, recent tests have revealed its suitability for unimodal optimization. The definition of Niching MG-PMA is provided in a detailed fashion, along with an in-depth explanation of two novelties in our implementation: the feedback of initial parameters and the domain constraints using periodic boundary conditions. These ideas can be potentially useful for other optimization techniques. The method is tested on the basis of the CEC’2015 benchmark functions. Statistical analysis shows that Niching MG-PMA performs similarly to the winners of the competition even without any parametrization towards the benchmark, indicating that the method is robust and applicable to a wide range of problems.
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Acknowledgements
This work was supported by the Brazilian fundations CNPq and by the Rio de Janeiro state agency FAPERJ (Grant Numbers E-26/203.198/2016 and E-26/010.002420/2016). This work was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001. We also acknowledge the support of Núcleo Avançado de Computação de Alto Desempenho (NACAD/COPPE/UFRJ), and Sistema Nacional de Processamento de Alto Desempenho (SINAPAD).
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Póvoa, R.C.B.L., Koshiyama, A.S., Dias, D.M. et al. Unimodal optimization using a genetic-programming-based method with periodic boundary conditions. Genet Program Evolvable Mach 21, 503–523 (2020). https://doi.org/10.1007/s10710-019-09373-1
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DOI: https://doi.org/10.1007/s10710-019-09373-1