{"title":"不确定性下移动供应链的鲁棒分散决策方法","authors":"Hani Shahmoradi-Moghadam, Jörn Schönberger","doi":"10.23773/2021_06","DOIUrl":null,"url":null,"abstract":"The mobile supply chain (MSC) is a new concept that allows companies more adaptability and flexibility. In MSCs, a product family can be produced, distributed, and delivered by a mobile factory, carried by trucks, and shared among different customers. In this paper, to optimize production scheduling and the mobile factory routing problem under uncertainty, a robust decentralized decision-making approach (RDDMA) based on the Analytical Target Cascading (ATC) approach is developed. The RDDMA is a bi-level hierarchical optimization method that divides an all-in-one model into sub-problems and aims to address each agent’s target. It is a 4-phase procedure, including time window determination, robust mobile factory routing, actual production scheduling, and adjustment. In real-world applications, the service time at each site is uncertain. Therefore, a scenario-based robust optimization approach is utilized to manage the uncertainties of the problem. Finally, the RDDMA performance is evaluated using several instances. The results suggest the proposed approach can provide robust solutions for such a multi-agent problem.","PeriodicalId":49772,"journal":{"name":"Naval Research Logistics","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A robust decentralized decision-making approach for mobile supply chains under uncertainty\",\"authors\":\"Hani Shahmoradi-Moghadam, Jörn Schönberger\",\"doi\":\"10.23773/2021_06\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The mobile supply chain (MSC) is a new concept that allows companies more adaptability and flexibility. In MSCs, a product family can be produced, distributed, and delivered by a mobile factory, carried by trucks, and shared among different customers. In this paper, to optimize production scheduling and the mobile factory routing problem under uncertainty, a robust decentralized decision-making approach (RDDMA) based on the Analytical Target Cascading (ATC) approach is developed. The RDDMA is a bi-level hierarchical optimization method that divides an all-in-one model into sub-problems and aims to address each agent’s target. It is a 4-phase procedure, including time window determination, robust mobile factory routing, actual production scheduling, and adjustment. In real-world applications, the service time at each site is uncertain. Therefore, a scenario-based robust optimization approach is utilized to manage the uncertainties of the problem. Finally, the RDDMA performance is evaluated using several instances. The results suggest the proposed approach can provide robust solutions for such a multi-agent problem.\",\"PeriodicalId\":49772,\"journal\":{\"name\":\"Naval Research Logistics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2021-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Naval Research Logistics\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.23773/2021_06\",\"RegionNum\":4,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"OPERATIONS RESEARCH & MANAGEMENT SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Naval Research Logistics","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.23773/2021_06","RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"OPERATIONS RESEARCH & MANAGEMENT SCIENCE","Score":null,"Total":0}
A robust decentralized decision-making approach for mobile supply chains under uncertainty
The mobile supply chain (MSC) is a new concept that allows companies more adaptability and flexibility. In MSCs, a product family can be produced, distributed, and delivered by a mobile factory, carried by trucks, and shared among different customers. In this paper, to optimize production scheduling and the mobile factory routing problem under uncertainty, a robust decentralized decision-making approach (RDDMA) based on the Analytical Target Cascading (ATC) approach is developed. The RDDMA is a bi-level hierarchical optimization method that divides an all-in-one model into sub-problems and aims to address each agent’s target. It is a 4-phase procedure, including time window determination, robust mobile factory routing, actual production scheduling, and adjustment. In real-world applications, the service time at each site is uncertain. Therefore, a scenario-based robust optimization approach is utilized to manage the uncertainties of the problem. Finally, the RDDMA performance is evaluated using several instances. The results suggest the proposed approach can provide robust solutions for such a multi-agent problem.
期刊介绍:
Submissions that are most appropriate for NRL are papers addressing modeling and analysis of problems motivated by real-world applications; major methodological advances in operations research and applied statistics; and expository or survey pieces of lasting value. Areas represented include (but are not limited to) probability, statistics, simulation, optimization, game theory, quality, scheduling, reliability, maintenance, supply chain, decision analysis, and combat models. Special issues devoted to a single topic are published occasionally, and proposals for special issues are welcomed by the Editorial Board.