A hybrid algorithm of particle swarm optimization and genetic algorithm with application in automatic replenishment model

Xingyan Cai; Xiaolu Sun; Yueyue Fan; Tao Liu

doi:10.1117/12.3031966

8 June 2024 A hybrid algorithm of particle swarm optimization and genetic algorithm with application in automatic replenishment model

Xingyan Cai, Xiaolu Sun, Yueyue Fan, Tao Liu

Author Affiliations +

Proceedings Volume 13171, Third International Conference on Algorithms, Microchips, and Network Applications (AMNA 2024); 131710T (2024) https://doi.org/10.1117/12.3031966
Event: 3rd International Conference on Algorithms, Microchips and Network Applications (AMNA 2024), 2024, Jinan, China

Abstract

This paper proposes a hybrid algorithm of particle swarm optimization and genetic algorithm named PSO-GA, which combines the advantages of genetic algorithm’s population diversity and stochastic global search and particle swarm optimization algorithm’s memory and fast convergence. The hybrid algorithm is then used to build an automatic replenishment model to help replenishment decisions by combining the idea of solving 0-1 knapsack problem. Using the sales data of a supermarket, we verify the feasibility and accuracy of the model, and the proposed algorithm can well solve practical problems in life.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xingyan Cai, Xiaolu Sun, Yueyue Fan, and Tao Liu "A hybrid algorithm of particle swarm optimization and genetic algorithm with application in automatic replenishment model", Proc. SPIE 13171, Third International Conference on Algorithms, Microchips, and Network Applications (AMNA 2024), 131710T (8 June 2024); https://doi.org/10.1117/12.3031966

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