Multi-Scale Quantum Harmonic Oscillator Behaved Algorithm with Three-Stage Perturbation for High-Dimensional Expensive Problems
Quantum perturbation plays an important role in quantum movement. This paper proposes a three-stage perturbation (TSP) framework to enhance the performance of multi-scale quantum harmonic oscillator algorithm (MQHOA). Three perturbations are adopted in the population initialization process with oppo...
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| Vydáno v: | 2024 IEEE International Conference on Systems, Man, and Cybernetics (SMC) s. 4187 - 4192 |
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| Hlavní autoři: | , , |
| Médium: | Konferenční příspěvek |
| Jazyk: | angličtina |
| Vydáno: |
IEEE
06.10.2024
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| On-line přístup: | Získat plný text |
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| Shrnutí: | Quantum perturbation plays an important role in quantum movement. This paper proposes a three-stage perturbation (TSP) framework to enhance the performance of multi-scale quantum harmonic oscillator algorithm (MQHOA). Three perturbations are adopted in the population initialization process with opposition-based learning (OBL), in quantum harmonic oscillator (QHO) process with ensemble of three differential evolution (DE) strategies and in multi-scale (M) process with a rollback mechanism to enhance the diversity of the particles and prevent from falling into local optima. The proposed approach has been evaluated on several high-dimensional expensive problems from 50-D to 500-D. The empirical data are compared with recent MQHOA variants and some state-of-the-art similar metaheuristic algorithms (MAs). The experimental results reveal the superiority or competitiveness of the the proposed approach. |
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| DOI: | 10.1109/SMC54092.2024.10831673 |