{"title":"基于改进蚁群算法的供给设施系统效率优化","authors":"Guozhuzhai Han, Ningjun Fan, Kai Lv","doi":"10.1109/QR2MSE.2013.6625811","DOIUrl":null,"url":null,"abstract":"It depends on proper plan of supply routes to improve system efficiency of supply facilities, when a few battle vehicles in different locations appear different failures. The time optimization of the process is a NP-hard problem. Since the runtime of algorithm is a part of the time for the supply process, the algorithm is required to construct a good enough solution in a limited time. Ant Colony System (ACS) is used to solve this problem, and a strategy is proposed to avoid it falling into local minimum. When the best-so-far solution is re-constructed, the pheromone value associated with each edge is updated to zero. Experiment results demonstrate that, compared with standard ACS, ACS with this strategy can construct a better solution in a shorter time and less iterations. In a word, its overall performance is better in solving the optimization problem of system efficiency.","PeriodicalId":140736,"journal":{"name":"2013 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE)","volume":"111 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Notice of RetractionImproved ant colony algorithm for system efficiency optimization of supply facilities\",\"authors\":\"Guozhuzhai Han, Ningjun Fan, Kai Lv\",\"doi\":\"10.1109/QR2MSE.2013.6625811\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"It depends on proper plan of supply routes to improve system efficiency of supply facilities, when a few battle vehicles in different locations appear different failures. The time optimization of the process is a NP-hard problem. Since the runtime of algorithm is a part of the time for the supply process, the algorithm is required to construct a good enough solution in a limited time. Ant Colony System (ACS) is used to solve this problem, and a strategy is proposed to avoid it falling into local minimum. When the best-so-far solution is re-constructed, the pheromone value associated with each edge is updated to zero. Experiment results demonstrate that, compared with standard ACS, ACS with this strategy can construct a better solution in a shorter time and less iterations. In a word, its overall performance is better in solving the optimization problem of system efficiency.\",\"PeriodicalId\":140736,\"journal\":{\"name\":\"2013 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE)\",\"volume\":\"111 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-07-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/QR2MSE.2013.6625811\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/QR2MSE.2013.6625811","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Notice of RetractionImproved ant colony algorithm for system efficiency optimization of supply facilities
It depends on proper plan of supply routes to improve system efficiency of supply facilities, when a few battle vehicles in different locations appear different failures. The time optimization of the process is a NP-hard problem. Since the runtime of algorithm is a part of the time for the supply process, the algorithm is required to construct a good enough solution in a limited time. Ant Colony System (ACS) is used to solve this problem, and a strategy is proposed to avoid it falling into local minimum. When the best-so-far solution is re-constructed, the pheromone value associated with each edge is updated to zero. Experiment results demonstrate that, compared with standard ACS, ACS with this strategy can construct a better solution in a shorter time and less iterations. In a word, its overall performance is better in solving the optimization problem of system efficiency.