{"title":"柔性制造系统中机械和物料搬运设备集成调度的多目标蚁群算法","authors":"T. Yung, S. Ponnambalam, M. Yogeswaran","doi":"10.1109/COASE.2009.5234130","DOIUrl":null,"url":null,"abstract":"A multi-objective integrated scheduling of machines and material handling equipment in an automated manufacturing system is addressed in this paper. The FMS environment is modeled with the incorporation of six multioperational machines and two automated guided vehicles (AGVs). An ant colony optimization (ACO) is proposed to optimize a multi-objective function that maximize machine utilization, maximize profit made, minimize AGV traveling time, and minimize AGV energy utilization concurrently. The performance of the proposed ACO algorithm is compared with conventional priority dispatching rules (pdrs) and it is found that proposed ACO performs better over the pdrs considered.","PeriodicalId":386046,"journal":{"name":"2009 IEEE International Conference on Automation Science and Engineering","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Multi-objective ACO for integrated scheduling of machines and material handling equipment in flexible manufacturing systems\",\"authors\":\"T. Yung, S. Ponnambalam, M. Yogeswaran\",\"doi\":\"10.1109/COASE.2009.5234130\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A multi-objective integrated scheduling of machines and material handling equipment in an automated manufacturing system is addressed in this paper. The FMS environment is modeled with the incorporation of six multioperational machines and two automated guided vehicles (AGVs). An ant colony optimization (ACO) is proposed to optimize a multi-objective function that maximize machine utilization, maximize profit made, minimize AGV traveling time, and minimize AGV energy utilization concurrently. The performance of the proposed ACO algorithm is compared with conventional priority dispatching rules (pdrs) and it is found that proposed ACO performs better over the pdrs considered.\",\"PeriodicalId\":386046,\"journal\":{\"name\":\"2009 IEEE International Conference on Automation Science and Engineering\",\"volume\":\"41 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-08-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE International Conference on Automation Science and Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/COASE.2009.5234130\",\"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 IEEE International Conference on Automation Science and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COASE.2009.5234130","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Multi-objective ACO for integrated scheduling of machines and material handling equipment in flexible manufacturing systems
A multi-objective integrated scheduling of machines and material handling equipment in an automated manufacturing system is addressed in this paper. The FMS environment is modeled with the incorporation of six multioperational machines and two automated guided vehicles (AGVs). An ant colony optimization (ACO) is proposed to optimize a multi-objective function that maximize machine utilization, maximize profit made, minimize AGV traveling time, and minimize AGV energy utilization concurrently. The performance of the proposed ACO algorithm is compared with conventional priority dispatching rules (pdrs) and it is found that proposed ACO performs better over the pdrs considered.