{"title":"A domain-inspired hyperheuristic for solving complex design problems of automation systems","authors":"A. C. Oezluek, K. Kabitzsch","doi":"10.1109/ETFA.2013.6648099","DOIUrl":null,"url":null,"abstract":"Automation systems comprise often huge and complex communication networks which save resources such as energy, time, capital and effort for humans. Design of automation systems is often a highly complex problem. For creation of optimal building automation system design, if component variety on the market is considered, there emerge many trade-off design solutions. In our previous work high quality design solutions could be obtained by proposed problem-specific adaptations of multi-objective metaheuristics. In this paper, we propose a new domain-inspired hyperheuristic approach to obtain the majority of optimal solutions in the true Pareto front that concerns evolving variation applications and selection operations.","PeriodicalId":106678,"journal":{"name":"2013 IEEE 18th Conference on Emerging Technologies & Factory Automation (ETFA)","volume":"257 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE 18th Conference on Emerging Technologies & Factory Automation (ETFA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ETFA.2013.6648099","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Automation systems comprise often huge and complex communication networks which save resources such as energy, time, capital and effort for humans. Design of automation systems is often a highly complex problem. For creation of optimal building automation system design, if component variety on the market is considered, there emerge many trade-off design solutions. In our previous work high quality design solutions could be obtained by proposed problem-specific adaptations of multi-objective metaheuristics. In this paper, we propose a new domain-inspired hyperheuristic approach to obtain the majority of optimal solutions in the true Pareto front that concerns evolving variation applications and selection operations.