{"title":"四种元启发式方法在求解流水车间调度问题中的比较研究","authors":"A. Bouzidi, M. Riffi, M. Barkatou","doi":"10.1109/WICT.2015.7489661","DOIUrl":null,"url":null,"abstract":"The Flow shop-scheduling problem is NP-hard combinatorial optimization problem, thus, it requires using the computational intelligence to solve it. This paper describes an experimental comparison study of four metaheuristics which are the hybrid genetic algorithm, particle swarm optimization (by and without using local search), and the cat swarm optimization algorithm, in order to analyze their performance in term of solution. The four algorithms has been applied to some benchmark Flow shop problems. The results show that the Cat swarm optimization algorithm is more efficient than other methods to solve the flow shop-scheduling problem.","PeriodicalId":246557,"journal":{"name":"2015 5th World Congress on Information and Communication Technologies (WICT)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A comparative study of four metaheuristics applied for solving the flow-shop scheduling problem\",\"authors\":\"A. Bouzidi, M. Riffi, M. Barkatou\",\"doi\":\"10.1109/WICT.2015.7489661\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Flow shop-scheduling problem is NP-hard combinatorial optimization problem, thus, it requires using the computational intelligence to solve it. This paper describes an experimental comparison study of four metaheuristics which are the hybrid genetic algorithm, particle swarm optimization (by and without using local search), and the cat swarm optimization algorithm, in order to analyze their performance in term of solution. The four algorithms has been applied to some benchmark Flow shop problems. The results show that the Cat swarm optimization algorithm is more efficient than other methods to solve the flow shop-scheduling problem.\",\"PeriodicalId\":246557,\"journal\":{\"name\":\"2015 5th World Congress on Information and Communication Technologies (WICT)\",\"volume\":\"42 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 5th World Congress on Information and Communication Technologies (WICT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WICT.2015.7489661\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 5th World Congress on Information and Communication Technologies (WICT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WICT.2015.7489661","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A comparative study of four metaheuristics applied for solving the flow-shop scheduling problem
The Flow shop-scheduling problem is NP-hard combinatorial optimization problem, thus, it requires using the computational intelligence to solve it. This paper describes an experimental comparison study of four metaheuristics which are the hybrid genetic algorithm, particle swarm optimization (by and without using local search), and the cat swarm optimization algorithm, in order to analyze their performance in term of solution. The four algorithms has been applied to some benchmark Flow shop problems. The results show that the Cat swarm optimization algorithm is more efficient than other methods to solve the flow shop-scheduling problem.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
