Application of Strength Pareto Evolutionary Algorithm II in Multi-Objective Water Supply Optimization Model Design for Mountainous Complex Terrain

Yihong Guan, Yangyang Chu (), Mou Lv (), Shuyan Li, Hang Li, Shen Dong and Yanbo Su
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Yihong Guan: School of Environment and Municipal Engineering, Qingdao University of Technology, Qingdao 266520, China
Yangyang Chu: School of Environment and Municipal Engineering, Qingdao University of Technology, Qingdao 266520, China
Mou Lv: School of Environment and Municipal Engineering, Qingdao University of Technology, Qingdao 266520, China
Shuyan Li: Zhonglian Northwest Engineering Design and Research Institute Co., Ltd., Xi’an 710076, China
Hang Li: School of Environment and Municipal Engineering, Qingdao University of Technology, Qingdao 266520, China
Shen Dong: School of Environment and Municipal Engineering, Qingdao University of Technology, Qingdao 266520, China
Yanbo Su: School of Environment and Municipal Engineering, Qingdao University of Technology, Qingdao 266520, China

Sustainability, 2023, vol. 15, issue 15, 1-20

Abstract: Water distribution networks (WDN) model optimization is an important part of smart water systems to achieve optimal strategies. WDN optimization focuses on the nonlinearity of the discharge head loss equation, the availability of discrete properties of pipe sizes, and the conservation of constraints. Multi-objective evolutionary algorithms (MOEAs) have been proposed and successfully applied in the field of WDN design optimization. Previous studies have focused on comparing the optimization effects of algorithms in water distribution networks, ignoring the problems of unbalanced pressure distribution and water hammer at the nodes of the pipe network caused by the complex terrain in mountainous areas. In this paper, a multi-objective water supply optimization model that integrated cost, reliability, and water quality was established for a mountainous WDN in real engineering. The method of traversing the nodes to solve the water age was introduced to find a more scientific and practical water age solution model, with setting the weight function to evaluate the water age of the water supply model comprehensively. Strength Pareto Evolutionary Algorithm II (SPEA-II) and Non-dominated Sorting Genetic Algorithm II (NSGA-II) were adopted to optimize the WDN design model in the mountainous complex terrain. The significance levels of the number of Pareto solutions (NOPS) and running time are 0.029 and 0.001, respectively, indicating that the two algorithms have significant differences. Compared to NSGA-II, SPEA-II has a better convergence rate and running time in multi-objective water supply optimization design. The solution set distribution of SPEA-II is more concentrated than that of NSGA-II, also the numerical value is better. The number of SPEA-II optimization schemes is larger and the scheme is more effective. Among them, the Pareto solution set of SPEA-II can obtain more desirable optimization results on cost, reliability index (RI) and water age. In summary, the study provides valuable information for decision makers in WDN with complex terrain.

Keywords: water distribution network; optimization design; mountainous complex terrain; SPEA-II; NSGA-II (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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