Retail supply chain network design with concurrent resilience capabilities

In this paper, we address the problem of designing/redesigning a resilient retail supply chain network under uncertainty. Considering pre- and post-disruption scenarios, this study proposes a two-stage stochastic optimization framework with multiple resilience strategies for designing a resilient retail supply chain. We consider facility fortification, inventory prepositioning, direct-to-store delivery, reserved capacity, inventory sharing and multiple set covering as our resilience strategies, covering all the three dimensions of resilience capabilities, namely, proactive, reactive, and network design quality. Taking into account the prominent role of retail outlets during Covid-19 epidemic outbreaks, through a real case study, we evaluate the impact of random and targeted disruptions on the performance of the retail supply chain network and provide managerial insights regarding the right balance between cost efficiency and resilience. Furthermore, we evaluate the effectiveness of these resilience capabilities in a number of simulated scenarios to show their applicability and importance under different disruptive situations. We show that when implemented concurrently, these resilience capabilities have a synergistic effect where the whole becomes larger than the sum of its parts. Subject to extensive stress testing, our results show that using any mixture of these resilience capabilities increases the retail network's resilience while considerably decreasing post-disruption costs.

Automated summary

This study proposes a two-stage stochastic optimization framework for designing a resilient retail supply chain network, considering various resilience strategies. Through stress testing, the research shows that implementing a combination of these resilience capabilities leads to a synergistic effect, increasing the network's resilience and decreasing post-disruption costs significantly.