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Multi-objective optimization of water distribution networks based on non-dominated sequencing genetic algorithm

Author

Listed:
  • Yi Tao
  • Dongfei Yan
  • Huijia Yang
  • Lingna Ma
  • Chen Kou

Abstract

Due to the conflict between reducing cost and improving water supply performance, how to select the appropriate pipe diameter is a current challenge. In this paper, the problem is transformed into a multi-objective optimization problem, and the evolutionary genetic optimization algorithm is used to solve the problem to determine the optimal selection of pipe diameter in the pipe network. To solve this problem, the evolutionary genetic algorithm was coupled with EPANET hydraulic simulation software in Python environment. The results show that NSGA-II and NSGA-III perform better in two typical case tests. Moreover, the increase of the objective functions will lead to an increase in the amount of data in the optimal solution set, and will affect the optimal value of each objective function. That shows that the balance between the economy and reliability of water supply can be successfully found by coupling the hydraulic model and the multi-objective optimization algorithm, which can provide an auxiliary decision for enterprises.

Suggested Citation

  • Yi Tao & Dongfei Yan & Huijia Yang & Lingna Ma & Chen Kou, 2022. "Multi-objective optimization of water distribution networks based on non-dominated sequencing genetic algorithm," PLOS ONE, Public Library of Science, vol. 17(11), pages 1-15, November.
    • Handle: RePEc:plo:pone00:0277954
    DOI: 10.1371/journal.pone.0277954
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