

Exact algorithms on reliable routing problems under uncertain topology using aggregation techniques for exponentially many scenarios. An emergency logistics distribution routing model for unexpected events. Back in business: Operations research in support of big data analytics for operations and supply chain management. International Journal of Physical Distribution and Logistics Management, 35(3), 195–207. Improving supply chain disaster preparedness: A decision process for secure site location. An interdependent layered network model for a resilient supply chain. In Proceedings of the 5th International ISCRAM Conference (pp.

A decision support framework to assess supply chain resilience. Transportation Research Part E: Logistics and Transportation Review, 91, 306–324.įalasca, M., Zobel, C. Marrying supply chain sustainability and resilience: A match made in heaven. Journal of Supply Chain Management, 47(2), 65–96.įahimnia, B., & Jabbarzadeh, A. Making sense of supply disruption risk research: A conceptual framework grounded in enactment theory. Connecting a population dynamic model with a multi-period location-allocation problem for post-disaster relief operations. C., Brasil, D., Châtelet, E., & Birregah, B. Annals of Operations Research, 1–20.ĭuhamel, C., Santos, A. Understanding risk management for intentional supply chain disruptions: Risk detection, risk mitigation, and risk recovery. Annals of Operations Research, 135(1), 155–178.ĭuHadway, S., Carnovale, S., & Hazen, B. Multitiered supply chain networks: Multicriteria decision-making under uncertainty. Annals of Operations Research, 1–21.Ĭraig, R.
#Risk probability disaster disruption code#
Bridging the research-practice gap in disaster relief: Using the IFRC code of conduct to develop an aid model. The international journal of logistics management, 15(2), 1–14.Ĭoles, J. International Journal of Production Research, 51(7), 2186–2199.Ĭhristopher, M., & Peck, H. Supply chain operational risk mitigation: A collaborative approach. Annals of Operations Research, 1–21.Ĭhen, J., Sohal, A. Modelling beneficiaries’ choice in disaster relief logistics. Design of a resilient shock absorber for disrupted supply chain networks: A shock-dampening fortification framework for mitigating excursion events. Locating facilities in the presence of disruptions and incomplete information. Annals of Operations Research, 223(1), 53–79.īerman, O., Krass, D., & Menezes, M. Relief distribution networks: A systematic review. A location-routing-inventory model for designing multisource distribution networks. Using both proactive and reactive approach, designing the distribution system can make the overall supply chain a disaster resilient supply chain.Īhmadi-Javid, A., & Seddighi, A. In case of disaster caused disruptions, the reactive approach is illustrated using three disruption case scenarios. The case illustration is discussed for proactive approach. The model is extended for reactive approach by considering the disruptions such as facility breakdowns, route blockages, and delivery delays with cost penalties. In proactive approach, the risk factors are considered as preventive measure for disaster caused disruptions.
#Risk probability disaster disruption windows#
The paper proposes Location-Routing Model with Time Windows using proactive and reactive approaches. The paper addresses these distribution decisions jointly as location-routing problem. The supply chain distribution network broadly comprises of two major decisions i.e. Therefore, business organizations are constantly focusing on making its distribution network of a supply chain resilient to either man-made or natural disasters in order to satisfy customer demand in time. Owing to disaster, the supply chain usually takes longer time to recover and eventually leads to loss in reputation and revenue. Natural or man-made disasters lead to disruptions across entire supply chain, hugely affecting the entire distribution system.
