{"title":"结合遗传算法和禁忌搜索的元启发式算法求解具有一般时滞的作业车间调度问题","authors":"M. Harrabi, O. Driss, K. Ghédira","doi":"10.1109/ICEMIS.2017.8272985","DOIUrl":null,"url":null,"abstract":"The Job shop scheduling problem with generic time lags is a generalization of the job shop problem. It is defined as a job shop problem with minimal and maximal delays between starting times of operations of different jobs. In this paper, we propose a combination of genetic algorithm and tabu search to solve Job Shop Problem with Generic Time Lags. Benchmark instances are used to investigate the performance of the proposed metaheuristic. The results show that the proposed combination of metaheuristics improves the efficiency.","PeriodicalId":117908,"journal":{"name":"2017 International Conference on Engineering & MIS (ICEMIS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Combining genetic algorithm and tabu search metaheuristic for job shop scheduling problem with generic time lags\",\"authors\":\"M. Harrabi, O. Driss, K. Ghédira\",\"doi\":\"10.1109/ICEMIS.2017.8272985\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Job shop scheduling problem with generic time lags is a generalization of the job shop problem. It is defined as a job shop problem with minimal and maximal delays between starting times of operations of different jobs. In this paper, we propose a combination of genetic algorithm and tabu search to solve Job Shop Problem with Generic Time Lags. Benchmark instances are used to investigate the performance of the proposed metaheuristic. The results show that the proposed combination of metaheuristics improves the efficiency.\",\"PeriodicalId\":117908,\"journal\":{\"name\":\"2017 International Conference on Engineering & MIS (ICEMIS)\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference on Engineering & MIS (ICEMIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICEMIS.2017.8272985\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Engineering & MIS (ICEMIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEMIS.2017.8272985","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Combining genetic algorithm and tabu search metaheuristic for job shop scheduling problem with generic time lags
The Job shop scheduling problem with generic time lags is a generalization of the job shop problem. It is defined as a job shop problem with minimal and maximal delays between starting times of operations of different jobs. In this paper, we propose a combination of genetic algorithm and tabu search to solve Job Shop Problem with Generic Time Lags. Benchmark instances are used to investigate the performance of the proposed metaheuristic. The results show that the proposed combination of metaheuristics improves the efficiency.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
