Scheduling of recovery actions in the supply chain with resilience analysis considerations

被引:77
|
作者
Ivanov, Dmitry [1 ]
Dolgui, Alexandre [2 ]
Sokolov, Boris [3 ,4 ]
机构
[1] Berlin Sch Econ & Law, Dept Business Adm, Berlin, Germany
[2] CNRS Chantrerie, IMT Atlantique, LS2N, Nantes, France
[3] ITMO Univ, St Petersburg, Russia
[4] RAS SPIIRAS, St Petersburg Inst Informat & Automat, St Petersburg, Russia
基金
俄罗斯科学基金会;
关键词
scheduling; supply chain engineering; supply chain dynamics; control; risk analysis; FACILITY LOCATION DESIGN; PROCESS FLEXIBILITY; LONG-CHAIN; DISRUPTION; MODEL; RELIABILITY; NETWORK; SYSTEM; RISK; PERFORMANCE;
D O I
10.1080/00207543.2017.1401747
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Supply chain engineering models with resilience considerations have been mostly focused on disruption impact quantification within one analysis layer, such as supply chain design or planning. Performance impact of disruptions has been typically analysed without scheduling of recovery actions. Taking into account schedule recovery actions and their duration times, this study extends the existing literature to supply chain scheduling and resilience analysis by an explicit integration of the optimal schedule recovery policy and supply chain resilience. In particular, we compute a schedule optimal control policy and analyse the performance of this policy by varying the perturbation vector and representing the outcomes of variations in the form of an attainable set. We propose a scheduling model that considers the coordination of recovery actions in the supply chain. Further, we suggest a resilience index by using the notion of attainable sets. The attainable sets are known in control theory; their calculation is based on the schedule control model results and the minimax regret approach for continuous time parameters given by intervals. We show that the proposed indicator can be used to estimate the impact of disruption and recovery dynamics on the achievement of planned performance in the supply chain.
引用
收藏
页码:6473 / 6490
页数:18
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