{"title":"改进蚁群算法在矿井机车调度问题中的应用","authors":"Guo-ning Gan, Ting-lei Huang, Shuai Gao","doi":"10.1109/ANTHOLOGY.2013.6784852","DOIUrl":null,"url":null,"abstract":"Ant Colony Algorithm has some advantages in solving complex optimization problems, in particular discrete optimization problem. A mine locomotive scheduling algorithm based on the improved Ant Colony Algorithm for the mine locomotive scheduling problem has proposed in this paper. The method takes simulated annealing algorithm as a local search strategy of ant colony algorithm, aim at expanding the solution search space, avoiding falling into local optimum that improve convergence rate of the algorithm by dynamic pheromone evaporation factor. Simulation results show that the algorithm is more efficiency in locomotive scheduling than the basic ant colony algorithm.","PeriodicalId":203169,"journal":{"name":"IEEE Conference Anthology","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The application of the improved Ant Colony Algorithm in mine locomotive scheduling problem\",\"authors\":\"Guo-ning Gan, Ting-lei Huang, Shuai Gao\",\"doi\":\"10.1109/ANTHOLOGY.2013.6784852\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Ant Colony Algorithm has some advantages in solving complex optimization problems, in particular discrete optimization problem. A mine locomotive scheduling algorithm based on the improved Ant Colony Algorithm for the mine locomotive scheduling problem has proposed in this paper. The method takes simulated annealing algorithm as a local search strategy of ant colony algorithm, aim at expanding the solution search space, avoiding falling into local optimum that improve convergence rate of the algorithm by dynamic pheromone evaporation factor. Simulation results show that the algorithm is more efficiency in locomotive scheduling than the basic ant colony algorithm.\",\"PeriodicalId\":203169,\"journal\":{\"name\":\"IEEE Conference Anthology\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Conference Anthology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ANTHOLOGY.2013.6784852\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Conference Anthology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ANTHOLOGY.2013.6784852","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The application of the improved Ant Colony Algorithm in mine locomotive scheduling problem
Ant Colony Algorithm has some advantages in solving complex optimization problems, in particular discrete optimization problem. A mine locomotive scheduling algorithm based on the improved Ant Colony Algorithm for the mine locomotive scheduling problem has proposed in this paper. The method takes simulated annealing algorithm as a local search strategy of ant colony algorithm, aim at expanding the solution search space, avoiding falling into local optimum that improve convergence rate of the algorithm by dynamic pheromone evaporation factor. Simulation results show that the algorithm is more efficiency in locomotive scheduling than the basic ant colony algorithm.
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