{"title":"求解约束满足问题的多信息素蚁群算法","authors":"Takuya Masukane, Kazunori Mizuno","doi":"10.1109/TAAI.2016.7880183","DOIUrl":null,"url":null,"abstract":"To solve large-scale constraint satisfaction problems, CSPs, ant colony optimization, ACO, based meta-heuristics has been effective. However, the naive ACO based method is sometimes inefficient because the method has only single pheromone trails. In this paper, we propose an ant colony optimization based meta-heuristics with multi pheromone trails in which artificial ants construct a candidate assignment by referring several pheromone trail graphs to solve CSP instances. We also implement the proposed model to some ACO based methods, demonstrating how our method is effective for solving graph coloring problems that is one of typical examples of CSPs.","PeriodicalId":159858,"journal":{"name":"2016 Conference on Technologies and Applications of Artificial Intelligence (TAAI)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Ant colony optimization with multi-pheromones for solving constraint satisfaction problems\",\"authors\":\"Takuya Masukane, Kazunori Mizuno\",\"doi\":\"10.1109/TAAI.2016.7880183\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To solve large-scale constraint satisfaction problems, CSPs, ant colony optimization, ACO, based meta-heuristics has been effective. However, the naive ACO based method is sometimes inefficient because the method has only single pheromone trails. In this paper, we propose an ant colony optimization based meta-heuristics with multi pheromone trails in which artificial ants construct a candidate assignment by referring several pheromone trail graphs to solve CSP instances. We also implement the proposed model to some ACO based methods, demonstrating how our method is effective for solving graph coloring problems that is one of typical examples of CSPs.\",\"PeriodicalId\":159858,\"journal\":{\"name\":\"2016 Conference on Technologies and Applications of Artificial Intelligence (TAAI)\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 Conference on Technologies and Applications of Artificial Intelligence (TAAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TAAI.2016.7880183\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Conference on Technologies and Applications of Artificial Intelligence (TAAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TAAI.2016.7880183","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Ant colony optimization with multi-pheromones for solving constraint satisfaction problems
To solve large-scale constraint satisfaction problems, CSPs, ant colony optimization, ACO, based meta-heuristics has been effective. However, the naive ACO based method is sometimes inefficient because the method has only single pheromone trails. In this paper, we propose an ant colony optimization based meta-heuristics with multi pheromone trails in which artificial ants construct a candidate assignment by referring several pheromone trail graphs to solve CSP instances. We also implement the proposed model to some ACO based methods, demonstrating how our method is effective for solving graph coloring problems that is one of typical examples of CSPs.
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