{"title":"约束求解的超启发式方法","authors":"Broderick Crawford, Carlos Castro, É. Monfroy","doi":"10.1109/CERMA.2010.99","DOIUrl":null,"url":null,"abstract":"In this work we propose a Choice Function for guiding Constraint Programming in the resolution of Constraint Satisfaction Problems. We exploit some search process features to select on the fly the Enumeration Strategy (Variable + Value Selection Heuristics) in order to more efficiently solve the problem at hand. The main novelty of our approach is that we reconfigure the search based solely on performance data gathered while solving the current problem. We report encouraging results where our combination of strategies outperforms the use of individual strategies.","PeriodicalId":119218,"journal":{"name":"2010 IEEE Electronics, Robotics and Automotive Mechanics Conference","volume":"451 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"A Hyperheuristic Approach for Constraint Solving\",\"authors\":\"Broderick Crawford, Carlos Castro, É. Monfroy\",\"doi\":\"10.1109/CERMA.2010.99\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this work we propose a Choice Function for guiding Constraint Programming in the resolution of Constraint Satisfaction Problems. We exploit some search process features to select on the fly the Enumeration Strategy (Variable + Value Selection Heuristics) in order to more efficiently solve the problem at hand. The main novelty of our approach is that we reconfigure the search based solely on performance data gathered while solving the current problem. We report encouraging results where our combination of strategies outperforms the use of individual strategies.\",\"PeriodicalId\":119218,\"journal\":{\"name\":\"2010 IEEE Electronics, Robotics and Automotive Mechanics Conference\",\"volume\":\"451 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-09-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE Electronics, Robotics and Automotive Mechanics Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CERMA.2010.99\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE Electronics, Robotics and Automotive Mechanics Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CERMA.2010.99","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this work we propose a Choice Function for guiding Constraint Programming in the resolution of Constraint Satisfaction Problems. We exploit some search process features to select on the fly the Enumeration Strategy (Variable + Value Selection Heuristics) in order to more efficiently solve the problem at hand. The main novelty of our approach is that we reconfigure the search based solely on performance data gathered while solving the current problem. We report encouraging results where our combination of strategies outperforms the use of individual strategies.