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

AbstractOne 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.

[1]  Chase Rainwater,et al.  Vulnerability assessment and re-routing of freight trains under disruptions: A coal supply chain network application , 2014 .

[2]  Harpreet Kaur,et al.  Proactive and reactive models for disaster resilient supply chain , 2019, Ann. Oper. Res..

[3]  Ming Dong,et al.  Supply Disruption and Reactive Strategies in an Assemble-to-Order Supply Chain With Time-Sensitive Demand , 2012, IEEE Transactions on Engineering Management.

[4]  Stefan Seuring,et al.  A review of modeling approaches for sustainable supply chain management , 2013, Decis. Support Syst..

[5]  Dan Wei,et al.  Economic Impacts of a California Tsunami , 2016 .

[6]  Stephan M. Wagner,et al.  Bottleneck identification in supply chain networks , 2013 .

[7]  George B. Dantzig,et al.  Decomposition Principle for Linear Programs , 1960 .

[8]  Kash Barker,et al.  Modeling infrastructure resilience using Bayesian networks: A case study of inland waterway ports , 2016, Comput. Ind. Eng..

[9]  Boris V. Sokolov,et al.  A multi-structural framework for adaptive supply chain planning and operations control with structure dynamics considerations , 2010, Eur. J. Oper. Res..

[10]  Hui Shan Loh,et al.  Cost Consequences of a Port-Related Supply Chain Disruption , 2015 .

[11]  Shital A. Thekdi,et al.  Supply Chain Vulnerability Analysis Using Scenario‐Based Input‐Output Modeling: Application to Port Operations , 2016, Risk analysis : an official publication of the Society for Risk Analysis.

[12]  Xiang Li,et al.  Innovative supply chain optimization models with multiple uncertainty factors , 2017, Ann. Oper. Res..

[13]  Trevor Hanson,et al.  Using Open Source Data to Quantify the Impact of Supply Chain Disruptions at Niche Ports: Scenario Involving Canada’s Largest Oil Refinery , 2016 .

[14]  Marcus Brandenburg,et al.  Quantitative models for sustainable supply chain management: Developments and directions , 2014, Eur. J. Oper. Res..

[15]  Armin Jabbarzadeh,et al.  Marrying supply chain sustainability and resilience: A match made in heaven , 2016 .

[16]  Boris V. Sokolov,et al.  Simulation Vs. Optimization Approaches to Ripple Effect Modelling in the Supply Chain , 2018, LDIC.

[17]  Dmitry Ivanov,et al.  A real-option approach to mitigate disruption risk in the supply chain , 2019, Omega.

[18]  Kuan Yew Wong,et al.  A robust optimization model for agile and build-to-order supply chain planning under uncertainties , 2013, Ann. Oper. Res..

[19]  K. Govindan.  Sustainable consumption and production in the food supply chain: A conceptual framework , 2018 .

[20]  William Ho,et al.  Supply chain risk management: a literature review , 2015 .

[21]  Alexandre Dolgui,et al.  The Ripple effect in supply chains: trade-off ‘efficiency-flexibility-resilience’ in disruption management , 2014 .

[22]  Ulla Tapaninen,et al.  Transport vulnerabilities and critical industries: experiences from a Finnish stevedore strike , 2011 .

[23]  Boris V. Sokolov,et al.  Optimal distribution (re)planning in a centralized multi-stage supply network under conditions of the ripple effect and structure dynamics , 2014, Eur. J. Oper. Res..

[24]  Dirk P. Kroese,et al.  Rare-event probability estimation with conditional Monte Carlo , 2011, Ann. Oper. Res..

[25]  Jennifer Blackhurst,et al.  The Severity of Supply Chain Disruptions: Design Characteristics and Mitigation Capabilities , 2007, Decis. Sci..

[26]  Jasmine Siu Lee Lam,et al.  Estimating economic losses of industry clusters due to port disruptions , 2016 .

[27]  D. Ivanov.  Revealing interfaces of supply chain resilience and sustainability: a simulation study , 2018, Int. J. Prod. Res..

[28]  David A Menachof,et al.  Scenario analysis and disaster preparedness for port and maritime logistics risk management. , 2016, Accident; analysis and prevention.

[29]  Jasmine Siu Lee Lam,et al.  Disruption risks and mitigation strategies: an analysis of Asian ports , 2015 .

[30]  Cheng-Hsien Hsieh,et al.  Disaster risk assessment of ports based on the perspective of vulnerability , 2014, Natural Hazards.

[31]  Kannan Govindan,et al.  Supply chain network design under uncertainty: A comprehensive review and future research directions , 2017, Eur. J. Oper. Res..

[32]  T. Papadopoulos,et al.  Supply chain sustainability: A risk management approach , 2016 .

[33]  Seyed Ali Torabi,et al.  Resilient supplier selection and order allocation under operational and disruption risks , 2015 .

[34]  David Simchi-Levi,et al.  Disruption Risk Mitigation in Supply Chains - The Risk Exposure Index Revisited , 2016, Oper. Res..

[35]  R. K. Pati,et al.  Evolution of sustainability in supply chain management: A literature review , 2017 .

[36]  Luis Herrera,et al.  Simulation-based multi-objective model for supply chains with disruptions in transportation , 2017 .

[37]  Marcus Brandenburg,et al.  Sustainable supply chain management: a modeling perspective , 2015, Annals of Operations Research.

[38]  R. Handfield,et al.  An empirically derived agenda of critical research issues for managing supply-chain disruptions , 2005 .

[39]  Mark Goh,et al.  Managing sudden transportation disruptions in supply chains under delivery delay and quantity loss , 2019, Ann. Oper. Res..

[40]  D. Ivanov.  Structural Dynamics and Resilience in Supply Chain Risk Management , 2017 .

[41]  Joseph Sarkis,et al.  A tradeoff model for green supply chain planning:A leanness-versus-greenness analysis , 2015 .

[42]  Dmitry Ivanov,et al.  Simulation-based ripple effect modelling in the supply chain , 2017, Int. J. Prod. Res..

[43]  Alexandre Dolgui,et al.  Hybrid Fuzzy-Probabilistic Approach to Supply Chain Resilience Assessment , 2018, IEEE Transactions on Engineering Management.

[44]  Alexandre Dolgui,et al.  Low-Certainty-Need (LCN) supply chains: a new perspective in managing disruption risks and resilience , 2018, Int. J. Prod. Res..

[45]  Dmitry Ivanov,et al.  Coordination of production and ordering policies under capacity disruption and product write-off risk: an analytical study with real-data based simulations of a fast moving consumer goods company , 2017, Annals of Operations Research.

[46]  Alexandre Dolgui,et al.  Ripple effect in the supply chain: an analysis and recent literature , 2018, Int. J. Prod. Res..

[47]  James B. Rice,et al.  Formal Vulnerability Assessment of a maritime transportation system , 2011, Reliab. Eng. Syst. Saf..

[48]  Chelsea C. White,et al.  Managing Inventory in Global Supply Chains Facing Port-of-Entry Disruption Risks , 2013, Transp. Sci..

[49]  Ruhul A. Sarker,et al.  Real time disruption management for a two-stage batch production-inventory system with reliability considerations , 2014, Eur. J. Oper. Res..

[50]  Sharada Vadali,et al.  Economic costs of critical infrastructure failure in bi-national regions and implications for resilience building: Evidence from El Paso–Ciudad Juarez , 2015 .

[51]  Nan Li,et al.  Management of sustainable manufacturing systems-a review on mathematical problems , 2017, Int. J. Prod. Res..

[52]  Tsan-Ming Choi,et al.  Optimal Bi-Objective Redundancy Allocation for Systems Reliability and Risk Management , 2016, IEEE Transactions on Cybernetics.

[53]  Feng Chu,et al.  Recent advances and opportunities in sustainable food supply chain: a model-oriented review , 2018, Int. J. Prod. Res..

[54]  Armin Jabbarzadeh,et al.  Resilient and sustainable supply chain design: sustainability analysis under disruption risks , 2018, Int. J. Prod. Res..

[55]  Tadeusz Sawik,et al.  A portfolio approach to supply chain disruption management , 2017, Int. J. Prod. Res..

[56]  HosseiniSeyedmohsen,et al.  Modeling infrastructure resilience using Bayesian networks , 2016 .

[57]  Alexandre Dolgui,et al.  Disruption-driven supply chain (re)-planning and performance impact assessment with consideration of pro-active and recovery policies , 2016 .

[58]  Kannan Govindan,et al.  Responsive and resilient supply chain network design under operational and disruption risks with delivery lead-time sensitive customers , 2017 .

[59]  Boris Sokolov,et al.  Minimization of disruption-related return flows in the supply chain , 2017 .

[60]  Mostafa Zandieh,et al.  A hybrid multi-stage predictive model for supply chain network collapse recovery analysis: a practical framework for effective supply chain network continuity management , 2011 .

[61]  Alexandre Dolgui,et al.  Literature review on disruption recovery in the supply chain* , 2017, Int. J. Prod. Res..

[62]  Tsan-Ming Choi,et al.  Advances in Risk Analysis with Big Data , 2017, Risk analysis : an official publication of the Society for Risk Analysis.