{"title":"将人工蜂群元启发式与Dhouib-Matrix-TSP1启发式相结合求解钻孔问题","authors":"S. Dhouib, A. Zouari, Saima Dhouib, H. Chabchoub","doi":"10.1080/21681015.2022.2158499","DOIUrl":null,"url":null,"abstract":"ABSTRACT In this article, an innovative hybrid optimization method is proposed based on the integration of the Artificial Bee Colony metaheuristic and the Dhouib-Matrix-TSP1 heuristic to overcome the tool path minimization problem. The proposed methodology consists firstly of providing different feasible solutions by implementing Dhouib-Matrix-TSP1 with several descriptive statistical metrics. Then, these solutions will become a part of the initial population of the Artificial Bee Colony that will perform this population in order to generate the optimal solution. To validate and compare the proposed method, several experimental instances of multi-hole making are simulated. The used dataset consists of four rectangular layouts and two circular layouts with an arrangement from 25 to 2600 holes. Results show that the proposed method outperforms the standard metaheuristics with an improvement rate between 0.24% and 9.35%. The obtained improvements concern simultaneously the minimal path length, the mean path length, and the SD of path lengths. Graphical Abstract","PeriodicalId":16024,"journal":{"name":"Journal of Industrial and Production Engineering","volume":null,"pages":null},"PeriodicalIF":4.0000,"publicationDate":"2022-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Integrating the artificial bee colony metaheuristic with Dhouib-Matrix-TSP1 heuristic for holes drilling problems\",\"authors\":\"S. Dhouib, A. Zouari, Saima Dhouib, H. Chabchoub\",\"doi\":\"10.1080/21681015.2022.2158499\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT In this article, an innovative hybrid optimization method is proposed based on the integration of the Artificial Bee Colony metaheuristic and the Dhouib-Matrix-TSP1 heuristic to overcome the tool path minimization problem. The proposed methodology consists firstly of providing different feasible solutions by implementing Dhouib-Matrix-TSP1 with several descriptive statistical metrics. Then, these solutions will become a part of the initial population of the Artificial Bee Colony that will perform this population in order to generate the optimal solution. To validate and compare the proposed method, several experimental instances of multi-hole making are simulated. The used dataset consists of four rectangular layouts and two circular layouts with an arrangement from 25 to 2600 holes. Results show that the proposed method outperforms the standard metaheuristics with an improvement rate between 0.24% and 9.35%. The obtained improvements concern simultaneously the minimal path length, the mean path length, and the SD of path lengths. Graphical Abstract\",\"PeriodicalId\":16024,\"journal\":{\"name\":\"Journal of Industrial and Production Engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.0000,\"publicationDate\":\"2022-12-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Industrial and Production Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/21681015.2022.2158499\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, INDUSTRIAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Industrial and Production Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/21681015.2022.2158499","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
Integrating the artificial bee colony metaheuristic with Dhouib-Matrix-TSP1 heuristic for holes drilling problems
ABSTRACT In this article, an innovative hybrid optimization method is proposed based on the integration of the Artificial Bee Colony metaheuristic and the Dhouib-Matrix-TSP1 heuristic to overcome the tool path minimization problem. The proposed methodology consists firstly of providing different feasible solutions by implementing Dhouib-Matrix-TSP1 with several descriptive statistical metrics. Then, these solutions will become a part of the initial population of the Artificial Bee Colony that will perform this population in order to generate the optimal solution. To validate and compare the proposed method, several experimental instances of multi-hole making are simulated. The used dataset consists of four rectangular layouts and two circular layouts with an arrangement from 25 to 2600 holes. Results show that the proposed method outperforms the standard metaheuristics with an improvement rate between 0.24% and 9.35%. The obtained improvements concern simultaneously the minimal path length, the mean path length, and the SD of path lengths. Graphical Abstract