{"title":"配水系统多目标优化:一种混合进化算法","authors":"Masoud Gheitasi, H. Kaboli, A. Keramat","doi":"10.1080/23249676.2021.1884613","DOIUrl":null,"url":null,"abstract":"The optimal operation of water distribution systems is complicated due to multiple objectives that are in conflict, such as water quality versus cost. This work proposes to combine Strength Pareto Evolutionary Algorithm (SPEAII) with Multi-Objective Particle Swarm Optimization (MOPSO) algorithm, called MOPSO-SPEAII, to establish a multi-objective model which handles water quality, costs and storage-reliable requirement. The main idea is that genetic operators are combined with particle swarm operators such that the fitness of SPEAII results is evaluated using MOPSO. An optimization-simulation model is prepared by linking the hybrid algorithm with EPANET software, and it is employed for a typical case study from the literature. The model outcomes verify that the MOPSO-SPEAII is more stable compared to SPEAII in terms of closeness to global minimum and can be used as a robust decision tool. However, the model application for a real sized system increases the computational intensity of the model.","PeriodicalId":51911,"journal":{"name":"Journal of Applied Water Engineering and Research","volume":null,"pages":null},"PeriodicalIF":1.4000,"publicationDate":"2021-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/23249676.2021.1884613","citationCount":"1","resultStr":"{\"title\":\"Multi-objective optimization of water distribution system: a hybrid evolutionary algorithm\",\"authors\":\"Masoud Gheitasi, H. Kaboli, A. Keramat\",\"doi\":\"10.1080/23249676.2021.1884613\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The optimal operation of water distribution systems is complicated due to multiple objectives that are in conflict, such as water quality versus cost. This work proposes to combine Strength Pareto Evolutionary Algorithm (SPEAII) with Multi-Objective Particle Swarm Optimization (MOPSO) algorithm, called MOPSO-SPEAII, to establish a multi-objective model which handles water quality, costs and storage-reliable requirement. The main idea is that genetic operators are combined with particle swarm operators such that the fitness of SPEAII results is evaluated using MOPSO. An optimization-simulation model is prepared by linking the hybrid algorithm with EPANET software, and it is employed for a typical case study from the literature. The model outcomes verify that the MOPSO-SPEAII is more stable compared to SPEAII in terms of closeness to global minimum and can be used as a robust decision tool. However, the model application for a real sized system increases the computational intensity of the model.\",\"PeriodicalId\":51911,\"journal\":{\"name\":\"Journal of Applied Water Engineering and Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2021-03-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1080/23249676.2021.1884613\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Applied Water Engineering and Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/23249676.2021.1884613\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"WATER RESOURCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Applied Water Engineering and Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/23249676.2021.1884613","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"WATER RESOURCES","Score":null,"Total":0}
Multi-objective optimization of water distribution system: a hybrid evolutionary algorithm
The optimal operation of water distribution systems is complicated due to multiple objectives that are in conflict, such as water quality versus cost. This work proposes to combine Strength Pareto Evolutionary Algorithm (SPEAII) with Multi-Objective Particle Swarm Optimization (MOPSO) algorithm, called MOPSO-SPEAII, to establish a multi-objective model which handles water quality, costs and storage-reliable requirement. The main idea is that genetic operators are combined with particle swarm operators such that the fitness of SPEAII results is evaluated using MOPSO. An optimization-simulation model is prepared by linking the hybrid algorithm with EPANET software, and it is employed for a typical case study from the literature. The model outcomes verify that the MOPSO-SPEAII is more stable compared to SPEAII in terms of closeness to global minimum and can be used as a robust decision tool. However, the model application for a real sized system increases the computational intensity of the model.
期刊介绍:
JAWER’s paradigm-changing (online only) articles provide directly applicable solutions to water engineering problems within the whole hydrosphere (rivers, lakes groundwater, estuaries, coastal and marine waters) covering areas such as: integrated water resources management and catchment hydraulics hydraulic machinery and structures hydraulics applied to water supply, treatment and drainage systems (including outfalls) water quality, security and governance in an engineering context environmental monitoring maritime hydraulics ecohydraulics flood risk modelling and management water related hazards desalination and re-use.