標題: A coordinated location-inventory problem with supply disruptions: A two-phase queuing theory-optimization model approach
作者: Liu, Yunhua
Dehghani, Ehsan
Jabalameli, Mohammad Saeed
Diabat, Ali
Lu, Chung-Cheng
運輸與物流管理系 註:原交通所+運管所
Department of Transportation and Logistics Management
關鍵字: Supply Chain;Disruption;Facility location;Inventory management;Queuing theory;Genetic algorithm
公開日期: 1-Apr-2020
摘要: Despite their prominent role in real-life, supply disruptions and inherent variability in parameters have been virtually overlooked in the area of the location-inventory problem. To push forward the relevant literature, addressing the aforementioned issues is of paramount importance. In this sense, this paper deals with a coordinated location-inventory problem in a stochastic supply chain system where facilities are subject to random supply disruptions. The demand and replenishment lead-times are also considered to be hemmed in by uncertainties. To tackle the location-inventory problem in the concerned supply chain, a two-phase approach based on the queuing theory and optimization model techniques is devised. Applying the queuing theory, the first phase tackles the uncertainty issues and gains some performance measures of the system. The attained results are later incorporated into the optimization model. In the second phase, the optimization model determines the strategic and tactical decisions across the supply chain in an integrated manner. Because the presented model is complicated to solve through exact methods, a tailored hybrid genetic algorithm embedded with direct search method is exploited, which is capable of finding quality solutions in an efficient way. Eventually, various sensitivity analyses are conducted from which interesting insights are derived.
URI: http://dx.doi.org/10.1016/j.cie.2020.106326
http://hdl.handle.net/11536/154133
ISSN: 0360-8352
DOI: 10.1016/j.cie.2020.106326
期刊: COMPUTERS & INDUSTRIAL ENGINEERING
Volume: 142
起始頁: 0
結束頁: 0
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