LSO is a novel physical-inspired metaheuristic algorithm that is inspired by the light dispersions with different angles while passing through rain droplets, causing the meteorological phenomenon of the colorful rainbow spectrum.
LSO is evaluated using four CEC benchmarks: CEC2014, CEC2017, CEC2020, and CEC2022, and its results are compared with eleven well-established and recently-published optimizers, named grey wolf optimizer (GWO), whale optimization algorithm (WOA), and salp swarm algorithm (SSA), evolutionary algorithms like differential evolution (DE), and recently-published optimizers including gradient-based optimizer (GBO), artificial gorilla troops optimizer (GTO), Runge–Kutta method (RUN) beyond the metaphor, African vultures optimization algorithm (AVOA), equilibrium optimizer (EO), grey wolf optimizer (GWO), Reptile Search Algorithm (RSA), and slime mold algorithm (SMA). In addition, several engineering design problems are solved, and the results are compared with many algorithms from the literature. The experimental results with the statistical analysis demonstrate the merits and highly superior performance of the proposed LSO algorithm.
Main Paper: Abdel-Basset, M., Mohamed, R. Light Spectrum Optimizer: A Novel Physics-Inspired Metaheuristic Optimization Algorithm, Mathematics 2022, 10(19). DOI: https://doi.org/10.3390/math10193466
인용 양식
Reda Mohamed (2024). Light Spectrum Optimizer (LSO) (https://www.mathworks.com/matlabcentral/fileexchange/126215-light-spectrum-optimizer-lso), MATLAB Central File Exchange. 검색 날짜: .
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