{"title":"破坏风险下供应链网络模型的混合元启发式求解方法","authors":"Chuluunsukh Anudari, YoungSu Yun, M. Gen","doi":"10.1109/CSCI54926.2021.00149","DOIUrl":null,"url":null,"abstract":"A supply chain network (SCN) model which considers facility and route disruptions simultaneously is proposed in this paper. Since most of conventional literature have focused either on facility disruption solely or on route disruption solely, the simultaneous consideration of facility and route disruptions can improve the flexibility of the implementation in the SCN model. The SCN model under the disruptions is represented as a mathematical formulation and a hybrid meta-heuristics (GA-VNS) approach which combines genetic algorithm (GA) with variable neighborhood search (VNS) is used for the mathematical formulation. In numerical experiment, two scaled SCN models are used for comparing the performance of the GA-VNS approach with those of some conventional meta-heuristics approaches. Experimental results prove that the GA-VNS approach is more robust than conventional meta-heuristics approaches, and the flexibility of the SCN model under the disruptions are also improved.","PeriodicalId":206881,"journal":{"name":"2021 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Hybrid Meta-heuristics Approach for Solving Supply Chain Network Model under Disruption Risk\",\"authors\":\"Chuluunsukh Anudari, YoungSu Yun, M. Gen\",\"doi\":\"10.1109/CSCI54926.2021.00149\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A supply chain network (SCN) model which considers facility and route disruptions simultaneously is proposed in this paper. Since most of conventional literature have focused either on facility disruption solely or on route disruption solely, the simultaneous consideration of facility and route disruptions can improve the flexibility of the implementation in the SCN model. The SCN model under the disruptions is represented as a mathematical formulation and a hybrid meta-heuristics (GA-VNS) approach which combines genetic algorithm (GA) with variable neighborhood search (VNS) is used for the mathematical formulation. In numerical experiment, two scaled SCN models are used for comparing the performance of the GA-VNS approach with those of some conventional meta-heuristics approaches. Experimental results prove that the GA-VNS approach is more robust than conventional meta-heuristics approaches, and the flexibility of the SCN model under the disruptions are also improved.\",\"PeriodicalId\":206881,\"journal\":{\"name\":\"2021 International Conference on Computational Science and Computational Intelligence (CSCI)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 International Conference on Computational Science and Computational Intelligence (CSCI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSCI54926.2021.00149\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Computational Science and Computational Intelligence (CSCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSCI54926.2021.00149","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Hybrid Meta-heuristics Approach for Solving Supply Chain Network Model under Disruption Risk
A supply chain network (SCN) model which considers facility and route disruptions simultaneously is proposed in this paper. Since most of conventional literature have focused either on facility disruption solely or on route disruption solely, the simultaneous consideration of facility and route disruptions can improve the flexibility of the implementation in the SCN model. The SCN model under the disruptions is represented as a mathematical formulation and a hybrid meta-heuristics (GA-VNS) approach which combines genetic algorithm (GA) with variable neighborhood search (VNS) is used for the mathematical formulation. In numerical experiment, two scaled SCN models are used for comparing the performance of the GA-VNS approach with those of some conventional meta-heuristics approaches. Experimental results prove that the GA-VNS approach is more robust than conventional meta-heuristics approaches, and the flexibility of the SCN model under the disruptions are also improved.