PVS: Population-based Vortex Search Algorithm
Population-based Vortex Search (PVS) is a new metaheuristic optimization algorithm: https://doi.org/10.1007/s00521-022-07671-x
PVS improves the weakness of the global search capability of Vortex Search which is a simple and efficient physics-based metaheuristic and originally has a single-solution-based structure. Single-solution-based metaheuristics perform a local search in the neighborhood of a single solution, whereas population-based metaheuristics conduct the search process by creating several candidate solutions at different points in the search space. The fast-running structures of single-solution-based algorithms may cause the search process to get stuck in the local optimum in some cases. The proposed algorithm transforms VS into a population-based structure with a location update operator and the polynomial mutation operator.
The performance of the proposed approach is investigated by applying a set of experimental series. Three different benchmark sets involving (i) 20 classical benchmark functions, (ii) 29 CEC2017 test functions, and (iii) 10 CEC2019 test functions are employed in experiments. In addition, four real-worldconstrained optimization problems are used to evaluate the effectiveness of PVS. Considering the experimental results obtained from the comparison of the proposed algorithm with both state-of-the-art and recent metaheuristics, PVS provides highly quite promising and superior outcomes in solution quality and robustness.
引用格式
Sağ, Tahir. “PVS: a New Population-Based Vortex Search Algorithm with Boosted Exploration Capability Using Polynomial Mutation.” Neural Computing and Applications, vol. 34, no. 20, Springer Science and Business Media LLC, Aug. 2022, pp. 18211–87, doi:10.1007/s00521-022-07671-x.
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