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Article

Fractional-Order Boosted Hybrid Young’s Double-Slit Experimental Optimizer for Truss Topology Engineering Optimization

1
School of Art and Design, Xi’an University of Technology, Xi’an 710054, China
2
National Demonstration Center for Experimental Arts Education, Nankai University, Tianjin 300371, China
3
Department of Applied Mathematics, Xi’an University of Technology, Xi’an 710054, China
*
Author to whom correspondence should be addressed.
Biomimetics 2024, 9(8), 474; https://doi.org/10.3390/biomimetics9080474
Submission received: 25 June 2024 / Revised: 30 July 2024 / Accepted: 1 August 2024 / Published: 5 August 2024

Abstract

Inspired by classical experiments that uncovered the inherent properties of light waves, Young’s Double-Slit Experiment (YDSE) optimization algorithm represents a physics-driven meta-heuristic method. Its unique search mechanism and scalability have attracted much attention. However, when facing complex or high-dimensional problems, the YDSE optimizer, although striking a good balance between global and local searches, does not converge as fast as it should and is prone to fall into local optimums, thus limiting its application scope. A fractional-order boosted hybrid YDSE, called FYDSE, is proposed in this article. FYDSE employs a multi-strategy mechanism to jointly address the YDSE problems and enhance its ability to solve complex problems. First, a fractional-order strategy is introduced into the dark edge position update of FYDSE to ensure more efficient use of the search potential of a single neighborhood space while reducing the possibility of trapping in a local best. Second, piecewise chaotic mapping is constructed at the initial stage of the population to obtain better-distributed initial solutions and increase the convergence rate to the optimal position. Moreover, the low exploration space is extended by using a dynamic opposition strategy, which improves the probability of acquisition of a globally optimal solution. Finally, by introducing the vertical operator, FYDSE can better balance global exploration and local exploitation and explore new unknown areas. The numerical results show that FYDSE outperforms YDSE in 11 (91.6%) of cec2022 sets. In addition, FYDSE performs best in 8 (66.6%) among all algorithms. Compared with the 11 methods, FYDSE obtains the optimal best and average weights for the 20-bar, 24-bar, and 72-bar truss problems, which proves its efficient optimization capability for difficult optimization cases.
Keywords: Young’s double-slit experiment; fractional-order strategy; piecewise chaotic mapping; dynamic opposition; vertical operator Young’s double-slit experiment; fractional-order strategy; piecewise chaotic mapping; dynamic opposition; vertical operator

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MDPI and ACS Style

Qin, S.; Liu, J.; Bai, X.; Hu, G. Fractional-Order Boosted Hybrid Young’s Double-Slit Experimental Optimizer for Truss Topology Engineering Optimization. Biomimetics 2024, 9, 474. https://doi.org/10.3390/biomimetics9080474

AMA Style

Qin S, Liu J, Bai X, Hu G. Fractional-Order Boosted Hybrid Young’s Double-Slit Experimental Optimizer for Truss Topology Engineering Optimization. Biomimetics. 2024; 9(8):474. https://doi.org/10.3390/biomimetics9080474

Chicago/Turabian Style

Qin, Song, Junling Liu, Xiaobo Bai, and Gang Hu. 2024. "Fractional-Order Boosted Hybrid Young’s Double-Slit Experimental Optimizer for Truss Topology Engineering Optimization" Biomimetics 9, no. 8: 474. https://doi.org/10.3390/biomimetics9080474

APA Style

Qin, S., Liu, J., Bai, X., & Hu, G. (2024). Fractional-Order Boosted Hybrid Young’s Double-Slit Experimental Optimizer for Truss Topology Engineering Optimization. Biomimetics, 9(8), 474. https://doi.org/10.3390/biomimetics9080474

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