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Bare-bones multi-scale quantum harmonic oscillator algorithm for global optimization
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AI
DOI：10.1016/j.eswa.2023.121870.png)
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Abstract
En 中文
The Multi-scale Quantum Harmonic Oscillator Algorithm (MQHOA) is a novel heuristic optimization technique, underpinned by the quantum wave function as its theoretical foundation. In this study, we present a streamlined MQHOA framework, dubbed the Bare-Bones Multi-scale Quantum Harmonic Oscillator Algorithm (BBMQHOA). This minimalist paradigm employs the most rudimentary free particle in quantum mechanics to simulate particle movement. BBMQHOA leverages group stability over individual stability, enabling the algorithm to fully capitalize on population data, thereby enhancing exploration and exploitation. An extensive array of experiments is carried out on a collection of 24 benchmark functions and a pair of real-world applications to validate the efficacy of our suggested methodology. The outcomes reveal that its performance is both practical and competitive while simultaneously maintaining user-friendliness.
Keywords:
Bare-bones multi-scale quantum harmonic oscillator algorithm
Heuristic algorithm
Global optimization
Journal
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7.5
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2.9W
Citations:
10.2W