{"title":"一种后期接受超启发式模糊自适应参数控制","authors":"Warren G. Jackson, E. Özcan, R. John","doi":"10.1109/UKCI.2014.6930167","DOIUrl":null,"url":null,"abstract":"A traditional iterative selection hyper-heuristic which manages a set of low level heuristics relies on two core components, a method for selecting a heuristic to apply at a given point, and a method to decide whether or not to accept the result of the heuristic application. In this paper, we present an initial study of a fuzzy system to control the list-size parameter of late-acceptance move acceptance method as a selection hyper-heuristic component. The performance of the fuzzy controlled selection hyper-heuristic is compared to its fixed parameter version and the best hyper-heuristic from a competition on the MAX-SAT problem domain. The results illustrate that a fuzzy control system can potentially be effective within a hyper-heuristic improving its performance.","PeriodicalId":315044,"journal":{"name":"2014 14th UK Workshop on Computational Intelligence (UKCI)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Fuzzy adaptive parameter control of a late acceptance hyper-heuristic\",\"authors\":\"Warren G. Jackson, E. Özcan, R. John\",\"doi\":\"10.1109/UKCI.2014.6930167\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A traditional iterative selection hyper-heuristic which manages a set of low level heuristics relies on two core components, a method for selecting a heuristic to apply at a given point, and a method to decide whether or not to accept the result of the heuristic application. In this paper, we present an initial study of a fuzzy system to control the list-size parameter of late-acceptance move acceptance method as a selection hyper-heuristic component. The performance of the fuzzy controlled selection hyper-heuristic is compared to its fixed parameter version and the best hyper-heuristic from a competition on the MAX-SAT problem domain. The results illustrate that a fuzzy control system can potentially be effective within a hyper-heuristic improving its performance.\",\"PeriodicalId\":315044,\"journal\":{\"name\":\"2014 14th UK Workshop on Computational Intelligence (UKCI)\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-10-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 14th UK Workshop on Computational Intelligence (UKCI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/UKCI.2014.6930167\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 14th UK Workshop on Computational Intelligence (UKCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/UKCI.2014.6930167","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fuzzy adaptive parameter control of a late acceptance hyper-heuristic
A traditional iterative selection hyper-heuristic which manages a set of low level heuristics relies on two core components, a method for selecting a heuristic to apply at a given point, and a method to decide whether or not to accept the result of the heuristic application. In this paper, we present an initial study of a fuzzy system to control the list-size parameter of late-acceptance move acceptance method as a selection hyper-heuristic component. The performance of the fuzzy controlled selection hyper-heuristic is compared to its fixed parameter version and the best hyper-heuristic from a competition on the MAX-SAT problem domain. The results illustrate that a fuzzy control system can potentially be effective within a hyper-heuristic improving its performance.