{"title":"自然启发的元启发式比较研究解决旅行商问题","authors":"A. Chandra, Aulia Naro","doi":"10.21776/ub.jemis.2021.009.02.1","DOIUrl":null,"url":null,"abstract":"There are numerous optimization method to solve the traveling salesman problem, TSP. One of methods is metaheuristics which is the state of the art algorithm that can solve the large and complex problem. In this research, three of well-known nature inspired population based metaheuristics algorithm: Ant Colony Optimization – ACO, Artificial Bee Colony – ABC and Particle Swarm Optimization – PSO are compared to solve the 29 destinations by using Matlab program. The ACO produces the shortest distance, 94 kilometers and is more efficient than ABC and PSO methods.","PeriodicalId":31715,"journal":{"name":"Journal of Engineering and Management in Industrial System","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"NATURE INSPIRED METAHEURISTICS COMPARATIVE STUDY TO SOLVE TRAVELING SALESMAN PROBLEM\",\"authors\":\"A. Chandra, Aulia Naro\",\"doi\":\"10.21776/ub.jemis.2021.009.02.1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"There are numerous optimization method to solve the traveling salesman problem, TSP. One of methods is metaheuristics which is the state of the art algorithm that can solve the large and complex problem. In this research, three of well-known nature inspired population based metaheuristics algorithm: Ant Colony Optimization – ACO, Artificial Bee Colony – ABC and Particle Swarm Optimization – PSO are compared to solve the 29 destinations by using Matlab program. The ACO produces the shortest distance, 94 kilometers and is more efficient than ABC and PSO methods.\",\"PeriodicalId\":31715,\"journal\":{\"name\":\"Journal of Engineering and Management in Industrial System\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Engineering and Management in Industrial System\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.21776/ub.jemis.2021.009.02.1\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Engineering and Management in Industrial System","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21776/ub.jemis.2021.009.02.1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
NATURE INSPIRED METAHEURISTICS COMPARATIVE STUDY TO SOLVE TRAVELING SALESMAN PROBLEM
There are numerous optimization method to solve the traveling salesman problem, TSP. One of methods is metaheuristics which is the state of the art algorithm that can solve the large and complex problem. In this research, three of well-known nature inspired population based metaheuristics algorithm: Ant Colony Optimization – ACO, Artificial Bee Colony – ABC and Particle Swarm Optimization – PSO are compared to solve the 29 destinations by using Matlab program. The ACO produces the shortest distance, 94 kilometers and is more efficient than ABC and PSO methods.
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