{"title":"考虑设防失效概率的稳健设施选址与设防","authors":"Haitao HU, Jiafu TANG, Jing LI","doi":"10.1016/j.omega.2025.103357","DOIUrl":null,"url":null,"abstract":"<div><div>Considering the viability of a supply chain (SC) is the ability to maintain itself and survive in a changing environment through a redesign of structures and replanning of performance with long-term impacts. This paper considers facility location and fortification problem (FLFP) in supply chain network against supply facility disruptions and fortification failure, where the fortification failure probability follows a binomial distribution (BD), a 0-1 uniform distribution (UD), and an unknown distribution but a normal distribution approximation (NDA). Three two-stage robust optimization model with decision-dependent uncertainty (TSRO-DDU) models are developed to model the FLFP problems under failure probability with BD, UD, and NDA. Some theoretical properties are developed to transform TSRO-DDU models equivalently into two-stage optimization models with decision-independent uncertainty (TSRO-DIU). To solve the TSRO-DIU models exactly, an improved column-and-constraint generation algorithm is developed to deal with the bilinear uncertainty of facility disruption and fortification failure. Numerical experiments are conducted to show the importance of considering fortification decisions and fortification failure probability. Furthermore, we demonstrate the flexibility of the TSRO-DDU models under random attack and fortification failure scenarios, compared with the no-fortification model (NFM), the classic successful fortification model (CFM), and the deterministic fortification failure model (DFM). We also extend the models by considering facility recovery decisions after the facility disruption risk. Overall, this work extends the facility location and fortification problems considering the fortification failure probability and can strategically help managers design a resilient and viable supply chain network in a complex and uncertain environment.</div></div>","PeriodicalId":19529,"journal":{"name":"Omega-international Journal of Management Science","volume":"137 ","pages":"Article 103357"},"PeriodicalIF":7.2000,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Robust facility location and fortification considering fortification failure probability\",\"authors\":\"Haitao HU, Jiafu TANG, Jing LI\",\"doi\":\"10.1016/j.omega.2025.103357\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Considering the viability of a supply chain (SC) is the ability to maintain itself and survive in a changing environment through a redesign of structures and replanning of performance with long-term impacts. This paper considers facility location and fortification problem (FLFP) in supply chain network against supply facility disruptions and fortification failure, where the fortification failure probability follows a binomial distribution (BD), a 0-1 uniform distribution (UD), and an unknown distribution but a normal distribution approximation (NDA). Three two-stage robust optimization model with decision-dependent uncertainty (TSRO-DDU) models are developed to model the FLFP problems under failure probability with BD, UD, and NDA. Some theoretical properties are developed to transform TSRO-DDU models equivalently into two-stage optimization models with decision-independent uncertainty (TSRO-DIU). To solve the TSRO-DIU models exactly, an improved column-and-constraint generation algorithm is developed to deal with the bilinear uncertainty of facility disruption and fortification failure. Numerical experiments are conducted to show the importance of considering fortification decisions and fortification failure probability. Furthermore, we demonstrate the flexibility of the TSRO-DDU models under random attack and fortification failure scenarios, compared with the no-fortification model (NFM), the classic successful fortification model (CFM), and the deterministic fortification failure model (DFM). We also extend the models by considering facility recovery decisions after the facility disruption risk. Overall, this work extends the facility location and fortification problems considering the fortification failure probability and can strategically help managers design a resilient and viable supply chain network in a complex and uncertain environment.</div></div>\",\"PeriodicalId\":19529,\"journal\":{\"name\":\"Omega-international Journal of Management Science\",\"volume\":\"137 \",\"pages\":\"Article 103357\"},\"PeriodicalIF\":7.2000,\"publicationDate\":\"2025-05-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Omega-international Journal of Management Science\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0305048325000830\",\"RegionNum\":2,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MANAGEMENT\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Omega-international Journal of Management Science","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0305048325000830","RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MANAGEMENT","Score":null,"Total":0}
Robust facility location and fortification considering fortification failure probability
Considering the viability of a supply chain (SC) is the ability to maintain itself and survive in a changing environment through a redesign of structures and replanning of performance with long-term impacts. This paper considers facility location and fortification problem (FLFP) in supply chain network against supply facility disruptions and fortification failure, where the fortification failure probability follows a binomial distribution (BD), a 0-1 uniform distribution (UD), and an unknown distribution but a normal distribution approximation (NDA). Three two-stage robust optimization model with decision-dependent uncertainty (TSRO-DDU) models are developed to model the FLFP problems under failure probability with BD, UD, and NDA. Some theoretical properties are developed to transform TSRO-DDU models equivalently into two-stage optimization models with decision-independent uncertainty (TSRO-DIU). To solve the TSRO-DIU models exactly, an improved column-and-constraint generation algorithm is developed to deal with the bilinear uncertainty of facility disruption and fortification failure. Numerical experiments are conducted to show the importance of considering fortification decisions and fortification failure probability. Furthermore, we demonstrate the flexibility of the TSRO-DDU models under random attack and fortification failure scenarios, compared with the no-fortification model (NFM), the classic successful fortification model (CFM), and the deterministic fortification failure model (DFM). We also extend the models by considering facility recovery decisions after the facility disruption risk. Overall, this work extends the facility location and fortification problems considering the fortification failure probability and can strategically help managers design a resilient and viable supply chain network in a complex and uncertain environment.
期刊介绍:
Omega reports on developments in management, including the latest research results and applications. Original contributions and review articles describe the state of the art in specific fields or functions of management, while there are shorter critical assessments of particular management techniques. Other features of the journal are the "Memoranda" section for short communications and "Feedback", a correspondence column. Omega is both stimulating reading and an important source for practising managers, specialists in management services, operational research workers and management scientists, management consultants, academics, students and research personnel throughout the world. The material published is of high quality and relevance, written in a manner which makes it accessible to all of this wide-ranging readership. Preference will be given to papers with implications to the practice of management. Submissions of purely theoretical papers are discouraged. The review of material for publication in the journal reflects this aim.