Production-distribution planning in a supply chain considering disruption and resilience factors

Nowadays resilience has become a critical aspect of infrastructures. Supply chains have been increasingly exposed to the risk of unpredicted disruptions causing significant economic forfeitures. At the same time, theexisting literature features a limited number of studies, which consider resilience of facilities for improvingproduction-distribution network ability. In this paper, we expand on traditional integrated productiondistributionmodels by including pre-disruption investment options, in addition to post-event recovery activities, as means to network resilience. The network under consideration includes three layers;manufacturing sites, distribution centers and customers’ zones. The problem is formulated as a threeobjectives stochastic optimization model. The model minimizes total expected cost and worst-case cost as well as maximizes the resilience of the production-distribution network simultaneously. The model seeks investment-recovery combinations that optimize the overall resilience of the production-distributionnetworks. In this study the Reservation Level driven Tchebycheff Procedure (RLTP) which is one of the reference point methods, is used to find the non-dominated solutions of our model. To approve the capability of our model a set of numerical experiments illustrates how changes to disruption scenarios probabilities affect the optimal resilient design investments.

Keywords:

Production-distribution , Resilience , Conditional value-at-risk , Mixed integer programming