{"title":"基于化学反应优化和Lin-Kernighan局部搜索的旅行商问题混合算法","authors":"Jian Sun, Yuting Wang, Jun-qing Li, K. Gao","doi":"10.1109/ICNC.2011.6022378","DOIUrl":null,"url":null,"abstract":"Chemical Reaction Optimization (CRO) is a new heuristic optimization method mimicking the process of a chemical reaction where molecules interact with each other aiming to reach the minimum state of free energy. CRO has demonstrated its capability in solving NP-hard optimization problems. The Lin-Kernighan(LK) local search is known to be one of the most successful heuristics for the Traveling Salesman Problem (TSP). In this paper, we present a hybrid algorithm based on CRO and LK local search for TSP. The proposed algorithm consider the tradeoff between the exploration abilities of CRO and the exploitation abilities of LK local searcher. Experimental results show that the proposed algorithm is efficient.","PeriodicalId":299503,"journal":{"name":"2011 Seventh International Conference on Natural Computation","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":"{\"title\":\"Hybrid algorithm based on Chemical Reaction Optimization and Lin-Kernighan local search for the Traveling Salesman Problem\",\"authors\":\"Jian Sun, Yuting Wang, Jun-qing Li, K. Gao\",\"doi\":\"10.1109/ICNC.2011.6022378\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Chemical Reaction Optimization (CRO) is a new heuristic optimization method mimicking the process of a chemical reaction where molecules interact with each other aiming to reach the minimum state of free energy. CRO has demonstrated its capability in solving NP-hard optimization problems. The Lin-Kernighan(LK) local search is known to be one of the most successful heuristics for the Traveling Salesman Problem (TSP). In this paper, we present a hybrid algorithm based on CRO and LK local search for TSP. The proposed algorithm consider the tradeoff between the exploration abilities of CRO and the exploitation abilities of LK local searcher. Experimental results show that the proposed algorithm is efficient.\",\"PeriodicalId\":299503,\"journal\":{\"name\":\"2011 Seventh International Conference on Natural Computation\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-07-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"19\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 Seventh International Conference on Natural Computation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICNC.2011.6022378\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Seventh International Conference on Natural Computation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNC.2011.6022378","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Hybrid algorithm based on Chemical Reaction Optimization and Lin-Kernighan local search for the Traveling Salesman Problem
Chemical Reaction Optimization (CRO) is a new heuristic optimization method mimicking the process of a chemical reaction where molecules interact with each other aiming to reach the minimum state of free energy. CRO has demonstrated its capability in solving NP-hard optimization problems. The Lin-Kernighan(LK) local search is known to be one of the most successful heuristics for the Traveling Salesman Problem (TSP). In this paper, we present a hybrid algorithm based on CRO and LK local search for TSP. The proposed algorithm consider the tradeoff between the exploration abilities of CRO and the exploitation abilities of LK local searcher. Experimental results show that the proposed algorithm is efficient.