{"title":"基于元胞自动机的多目标优化:在水库多用途运行中的应用","authors":"M. Afshar, R. Hajiabadi","doi":"10.1080/10286608.2019.1604691","DOIUrl":null,"url":null,"abstract":"ABSTRACT In this paper, a weighted cellular automata (CA) is proposed to solve bi-objective reservoir operation optimisation problem considering two objectives of water supply and hydropower production. A mathematically derived updating rule is used contributing to the efficiency of the proposed CA method. The updating rule of the problem is derived by converting the bi-objective problem to a single-objective problem using the well-known weighting method. The proposed method is used to operate the Dez reservoir in Iran over various operation periods of 60, 120, 240 and 480 months to test the performance of the method for operational problems of different scales. Performance of the method is also compared with that of a non-dominated sorting genetic algorithm (NSGAII) as one of the most popular multi-objective evolutionary algorithms. The results indicate that the proposed method is highly efficient compared to the NSGAII while producing comparable results. This is in line with the early findings of superior efficiency and comparable effectiveness of the CA method with the existing evolutionary algorithms for single objective optimisation problems.","PeriodicalId":50689,"journal":{"name":"Civil Engineering and Environmental Systems","volume":null,"pages":null},"PeriodicalIF":1.7000,"publicationDate":"2019-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Multi-objective optimisation using cellular automata: application to multi-purpose reservoir operation\",\"authors\":\"M. Afshar, R. Hajiabadi\",\"doi\":\"10.1080/10286608.2019.1604691\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT In this paper, a weighted cellular automata (CA) is proposed to solve bi-objective reservoir operation optimisation problem considering two objectives of water supply and hydropower production. A mathematically derived updating rule is used contributing to the efficiency of the proposed CA method. The updating rule of the problem is derived by converting the bi-objective problem to a single-objective problem using the well-known weighting method. The proposed method is used to operate the Dez reservoir in Iran over various operation periods of 60, 120, 240 and 480 months to test the performance of the method for operational problems of different scales. Performance of the method is also compared with that of a non-dominated sorting genetic algorithm (NSGAII) as one of the most popular multi-objective evolutionary algorithms. The results indicate that the proposed method is highly efficient compared to the NSGAII while producing comparable results. This is in line with the early findings of superior efficiency and comparable effectiveness of the CA method with the existing evolutionary algorithms for single objective optimisation problems.\",\"PeriodicalId\":50689,\"journal\":{\"name\":\"Civil Engineering and Environmental Systems\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2019-05-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Civil Engineering and Environmental Systems\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1080/10286608.2019.1604691\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, CIVIL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Civil Engineering and Environmental Systems","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1080/10286608.2019.1604691","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
Multi-objective optimisation using cellular automata: application to multi-purpose reservoir operation
ABSTRACT In this paper, a weighted cellular automata (CA) is proposed to solve bi-objective reservoir operation optimisation problem considering two objectives of water supply and hydropower production. A mathematically derived updating rule is used contributing to the efficiency of the proposed CA method. The updating rule of the problem is derived by converting the bi-objective problem to a single-objective problem using the well-known weighting method. The proposed method is used to operate the Dez reservoir in Iran over various operation periods of 60, 120, 240 and 480 months to test the performance of the method for operational problems of different scales. Performance of the method is also compared with that of a non-dominated sorting genetic algorithm (NSGAII) as one of the most popular multi-objective evolutionary algorithms. The results indicate that the proposed method is highly efficient compared to the NSGAII while producing comparable results. This is in line with the early findings of superior efficiency and comparable effectiveness of the CA method with the existing evolutionary algorithms for single objective optimisation problems.
期刊介绍:
Civil Engineering and Environmental Systems is devoted to the advancement of systems thinking and systems techniques throughout systems engineering, environmental engineering decision-making, and engineering management. We do this by publishing the practical applications and developments of "hard" and "soft" systems techniques and thinking.
Submissions that allow for better analysis of civil engineering and environmental systems might look at:
-Civil Engineering optimization
-Risk assessment in engineering
-Civil engineering decision analysis
-System identification in engineering
-Civil engineering numerical simulation
-Uncertainty modelling in engineering
-Qualitative modelling of complex engineering systems