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

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.

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Publication Details

Journal
Biomimetics
Published
2024-08-05
DOI
https://doi.org/10.3390/biomimetics9080474
Citations
2
Primary Topic
Topology Optimization in Engineering
Type
article
Field-Weighted Citation Impact
0.52
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article

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

Junling Liu, Xiaobo Bai, Gang Hu, Song Qin
2 citations
Biomimetics
Topology Optimization in Engineering
0.52
article

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

Junling Liu, Xiaobo Bai, Gang Hu, Song Qin
article en
2 citations

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.

BiomimeticsVol. 9(8)
Nankai University (CN), Xi'an University of Technology (CN)
Openalex Percentile: Top 37%
Topology Optimization in Engineering
0.52
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