{"title":"基于蚁群优化算法的资源约束项目调度问题求解","authors":"Yongbo Yuan, Kai Wang, Le Ding","doi":"10.1109/HIS.2009.92","DOIUrl":null,"url":null,"abstract":"Ant Colony Optimization (ACO) is a popular-based, artificial agent, general-search technique for the solution of difficult combinatorial problems. This paper presents a solution to the Resource-Constraint Project Scheduling Problem based on ACO algorithm. The method considers the quantified duration and resource as the heuristic information to calculate the accurate state transition probability and finally reaches the scheduling optimization. The described ACO algorithm is tested on a sample case taken from the literature and the parameters in ACO are determined by tests. The computational results validate the effectiveness of the proposed algorithm.","PeriodicalId":414085,"journal":{"name":"2009 Ninth International Conference on Hybrid Intelligent Systems","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A Solution to Resource-Constrained Project Scheduling Problem: Based on Ant Colony Optimization Algorithm\",\"authors\":\"Yongbo Yuan, Kai Wang, Le Ding\",\"doi\":\"10.1109/HIS.2009.92\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Ant Colony Optimization (ACO) is a popular-based, artificial agent, general-search technique for the solution of difficult combinatorial problems. This paper presents a solution to the Resource-Constraint Project Scheduling Problem based on ACO algorithm. The method considers the quantified duration and resource as the heuristic information to calculate the accurate state transition probability and finally reaches the scheduling optimization. The described ACO algorithm is tested on a sample case taken from the literature and the parameters in ACO are determined by tests. The computational results validate the effectiveness of the proposed algorithm.\",\"PeriodicalId\":414085,\"journal\":{\"name\":\"2009 Ninth International Conference on Hybrid Intelligent Systems\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-08-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Ninth International Conference on Hybrid Intelligent Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HIS.2009.92\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Ninth International Conference on Hybrid Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HIS.2009.92","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Solution to Resource-Constrained Project Scheduling Problem: Based on Ant Colony Optimization Algorithm
Ant Colony Optimization (ACO) is a popular-based, artificial agent, general-search technique for the solution of difficult combinatorial problems. This paper presents a solution to the Resource-Constraint Project Scheduling Problem based on ACO algorithm. The method considers the quantified duration and resource as the heuristic information to calculate the accurate state transition probability and finally reaches the scheduling optimization. The described ACO algorithm is tested on a sample case taken from the literature and the parameters in ACO are determined by tests. The computational results validate the effectiveness of the proposed algorithm.
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