期刊
JOURNAL OF FLOOD RISK MANAGEMENT
卷 10, 期 3, 页码 326-338出版社
WILEY
DOI: 10.1111/jfr3.12143
关键词
MOPSO; multi-objective optimisation; NSGA-II; NSHS; sewer pipe network; urban drainage system
资金
- National Research Foundation of Korean (NRF) grant - Korean government (MSIP) [NRF-2013R1A2A1A01013886]
- Advanced Water Management Research Program (AWMP) - Ministry of Land, Infrastructure, and Transport of the Korean government [13AWMP-B066744-01]
In recent decades, evolutionary optimisation algorithms have been used successfully for a wide variety of water resources engineering problems and their applications are still increasing. In this research work, a hybrid harmony search algorithm, 'Non-dominated Sorting Harmony Search' algorithm is developed and comparedwith two state-of-the-artmulti-objective evolutionary algorithms the non-dominated sorting genetic algorithm (NSGA)-II and multi-objective particle swarmoptimisation (MOPSO) algorithms - for assigning optimal rehabilitation plans for sewer pipe networks. The algorithms considered were validated using some standard test functions reported in the literature and compared with each other in terms of several metrics. These algorithms were then linked to theSWMM-EPAhydraulic model and applied to a stormsewer pipe network case study in Seoul, South Korea, to obtain the best rehabilitation plans for pipe replacements. The results showed that the algorithms considered have different behaviours in solving the benchmark tests and rehabilitation problem. The proposed hybrid multi-objective harmony search algorithm provides better optimal solutions in terms of different metrics and clearly outperforms the other two algorithms for the rehabilitation of the storm sewer pipe networks.
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