Abstract
Single-solution-based optimization algorithms are computationally cheap yet powerful methods that can be used on various optimization tasks at minimal processing expenses. However, there is a considerable shortage of research in this domain, resulting in only a handful of proposed algorithms over the last four decades. This study proposes the Prism Refraction Search (PRS), a novel, simple yet efficient, single-solution-based metaheuristic algorithm for single-objective real-parameter optimization. PRS is a physics-inspired algorithm modeled on a well-known optimization paradigm in ray optics arising from the refraction of light through a triangular prism. The key novelty lies in its scientifically sound background that is supported by the well-established laws of physical optics. The proposed algorithm is evaluated on several numerical objectives, including 23 classical benchmark functions, the CEC-2017 test suite, and five standard real-world engineering design problems. Further, the results are analyzed using standard statistical tests to prove their significance. Extensive experiments and comparisons with state-of-the-art metaheuristic algorithms in the literature justify the robustness and competitive performance of the PRS algorithm as a lightweight and efficient optimization strategy.
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The data used to support the finding are cited within the article. Also, the datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
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RH, SC and MAN performed the experiments. SN and DO Wrote the manuscript. All authors conceptualized the proposal and reviewed the manuscript. All authors contributed equally to the study conception and design.
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Kundu, R., Chattopadhyay, S., Nag, S. et al. Prism refraction search: a novel physics-based metaheuristic algorithm. J Supercomput 80, 10746–10795 (2024). https://doi.org/10.1007/s11227-023-05790-3
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DOI: https://doi.org/10.1007/s11227-023-05790-3