Optimal Design of Water Supply Network Based on Adaptive Penalty Function and Improved Genetic Algorithm

Kun Ding, Yong Ni, Lingfeng Fan, Tian-Le Sun and Tabasam Rashid

Mathematical Problems in Engineering, 2022, vol. 2022, 1-8

Abstract: In view of the shortcomings of water supply network optimization design based on the traditional genetic algorithm in water supply safety and economy, an improved crossover operator adaptive algorithm and penalty function are proposed to improve the traditional genetic algorithm, which can effectively solve the problem of local optimal solution caused by too early convergence of the traditional genetic algorithm in pipe network optimization design. Taking a typical annular water supply network as an example, the calculation results show that the economy of the design scheme of the improved genetic algorithm is better than the traditional genetic algorithm, which fully shows that the improved genetic algorithm is practical and effective for the optimal design of water supply network.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:8252086

DOI: 10.1155/2022/8252086

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