Abstract
This paper proposes an adaptive method to select recombination operators, including differential evolution (DE) operators and polynomial operators. Moreover, a push and pull search (PPS) method is used to handle constrained single-objective optimization problems (CSOPs). The PPS has two search stages—the push stage and the pull stage. In the push stage, a CSOP is optimized without considering constraints. In the pull stage, the CSOP is optimized with an improved epsilon constraint-handling method. In this paper, twenty-eight CSOPs are used to test the performance of the proposed adaptive GA with the PPS method (AGA-PPS). AGA-PPS is compared with three other differential evolution algorithms, including LSHADE44+IDE, LSHADE44 and UDE. The experimental results indicate that the proposed AGA-PPS is significantly better than other compared algorithms on the twenty-eight CSOPsq.
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Fan, Z., Wang, Z., Fang, Y., Li, W., Yuan, Y., Bian, X. (2018). Adaptive Recombination Operator Selection in Push and Pull Search for Solving Constrained Single-Objective Optimization Problems. In: Qiao, J., et al. Bio-inspired Computing: Theories and Applications. BIC-TA 2018. Communications in Computer and Information Science, vol 951. Springer, Singapore. https://doi.org/10.1007/978-981-13-2826-8_31
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DOI: https://doi.org/10.1007/978-981-13-2826-8_31
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