Optimization of network redundancy and contingency planning in sustainable and resilient supply chain resource management under conditions of structural dynamics

被引:11
作者
Pavlov, Alexander [1 ,3 ]
Ivanov, Dmitry [2 ]
Pavlov, Dmitry [3 ]
Slinko, Alexey [3 ]
机构
[1] St Petersburg Inst Informat & Automat SPIIRAS, Line 14 VO 39, St Petersburg 199178, Russia
[2] Sch Econ & Law, Dept Business & Econ, Chair Supply Chain Management, Badensche Str 50, D-10825 Berlin, Germany
[3] Mozhaisky Aerosp Acad, Ul Zdanovskaya 13, St Petersburg 197198, Russia
基金
俄罗斯基础研究基金会;
关键词
Supply chain; Sustainability; Risk management; Optimization; Logistics network; Linear programming; Decomposition; DISRUPTION RISKS; RECOVERY; DESIGN; MODEL; RELIABILITY; STRATEGIES; ALLOCATION; INVENTORY; FRAMEWORK;
D O I
10.1007/s10479-019-03182-6
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
One of the key issues in supply chain sustainability is the efficient usage of the available resources. At the same time, proactive supply chain design with disruption risk considerations frequently leads to a network redundancy which implies some resource reservations in anticipation of possible disruptions. Even if resilient supply chain design has received much attention in literature, there is a research gap in designing both resilient and sustainable supply chains. This study contributes to closing the given gap by proposing a novel methodological approach to modelling network redundancy optimization. This allows for simultaneous computation of both optimal network redundancy and proactive contingency plans, considering both supply dynamics and structural disruption risks. The novelties of this study are the integration of sustainable resource utilization and SC resilience based on coordination of structure- and flow-oriented optimization. The model uncovers a practical approach to analyze and optimize supply chain redundancy by varying processing intensities of resource consumption in the network according to supply and structural dynamics. This makes it possible to explicitly include the dynamics of resource consumption for contingency plan realization in disruption scenarios.
引用
收藏
页码:495 / 524
页数:30
相关论文
共 62 条
[21]   Supply chain network design under uncertainty: A comprehensive review and future research directions [J].
Govindan, Kannan ;
Fattahi, Mohammad ;
Keyvanshokooh, Esmaeil .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2017, 263 (01) :108-141
[22]   Optimal Bi-Objective Redundancy Allocation for Systems Reliability and Risk Management [J].
Govindan, Kannan ;
Jafarian, Ahmad ;
Azbari, Mostafa E. ;
Choi, Tsan-Ming .
IEEE TRANSACTIONS ON CYBERNETICS, 2016, 46 (08) :1735-1748
[23]   Using Open Source Data to Quantify the Impact of Supply Chain Disruptions at Niche Ports Scenario Involving Canada's Largest Oil Refinery [J].
Hanson, Trevor R. .
TRANSPORTATION RESEARCH RECORD, 2016, (2549) :29-36
[24]   A real-option approach to mitigate disruption risk in the supply chain [J].
He, Jian ;
Alayifard, Farzad ;
Iyanov, Dmitry ;
Jahani, Hamed .
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE, 2019, 88 :133-149
[25]   Supply chain risk management: a literature review [J].
Ho, William ;
Zheng, Tian ;
Yildiz, Hakan ;
Talluri, Srinivas .
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2015, 53 (16) :5031-5069
[26]   Modeling infrastructure resilience using Bayesian networks: A case study of inland waterway ports [J].
Hosseini, Seyedmohsen ;
Barker, Kash .
COMPUTERS & INDUSTRIAL ENGINEERING, 2016, 93 :252-266
[27]   Disaster risk assessment of ports based on the perspective of vulnerability [J].
Hsieh, Cheng-Hsien .
NATURAL HAZARDS, 2014, 74 (02) :851-864
[28]  
Ivanov D., 2018, Structural Dynamics and Resilience in Supply Chain Risk Management, P1, DOI [10.1007/978-3-319-69305-7, DOI 10.1007/978-3-319-69305-7]
[29]   Revealing interfaces of supply chain resilience and sustainability: a simulation study [J].
Ivanov, Dmitry .
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2018, 56 (10) :3507-3523
[30]   Low-Certainty-Need (LCN) supply chains: a new perspective in managing disruption risks and resilience [J].
Ivanov, Dmitry ;
Dolgui, Alexandre .
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2019, 57 (15-16) :5119-5136