A supply chain disruption risk mitigation model to manage COVID-19 pandemic risk

Abstract

This study develops a mathematical model to mitigate disruptions in a three-stage (i.e., supplier, manufacturer, retailer) supply chain network subject to a natural disaster like COVID-19 pandemic. This optimization model aims to manage supply chain disruptions for a pandemic situation where disruptions can occur to both the supplier and the retailer. This study proposes an inventory policy using the renewal reward theory for maximizing profit for the manufacturer under study. Tested using two heuristics algorithms, namely the genetic algorithm (GA) and pattern search (PS), the proposed inventory-based disruption risk mitigation model provides the manufacturer with an optimum decision to maximize profits in a production cycle. A sensitivity analysis was offered to ensure the applicability of the model in practical settings. Results reveal that the PS algorithm performed better for such model than a heuristic method like GA. The ordering quantity and reordering point were also lower in PS than GA. Overall, it was evident that PS is more suited for this problem. Supply chain managers need to employ appropriate inventory policies to deal with several uncertain conditions, for example, uncertainties arising due to the COVID-19 pandemic. This model can help managers establish and redesign an inventory policy to maximize the profit by considering probable disruptions in the supply chain network.

A Bi-Level Model for Green Freight Transportation Pricing Strategy Considering Enterprise Profit and Carbon Emissions

“…Finally, the purpose of this paper was to maximize enterprise operating profits, which can ensure the survival of logistics enterprises during the pandemic period. In references [37][38][39], methods of supply chain reconfiguration during the COVID-19 pandemic period were proposed. However, the reconfiguration of supply chain network structure often has a long implementation cycle and large initial investment, which suggests higher requirements for enterprise cash flow.…”

“…In terms of the impact on supply chain stability, COVID-19 has caused the interruption of supply chains throughout the world, which has created great challenges to global supply chain management. Many researchers are concerned about how best to manage the supply chain disruptions caused by COVID-19, including suppliers, manufacturers, and retailers [37]. At the same time, the integration ability, resilience, and sustainability of the world's supply chains are facing great challenges; a lot of research has been carried out on the sustainability of supply chains [38,39].…”

“…Then, using the same algorithm, we can obtain the response function for other transportation modes, as per Equations ( 36) and (37).…”

“…Equations ( 35) to (37) are used to calculate the total carbon emissions of a green freight system in the upper objective function. At this point, we have completed the solution of the bi-level programming model.…”

“…Step 2: Under the condition of p w n(j) n ∈ N, w ∈ W (the virtual transportation mode does not need pricing), the lower-level programming model is solved to obtain the freight volume allocation scheme q w * n(j) n ∈ N * , w ∈ W , including the equilibrium solution q w * 1(j) of the user equilibrium traffic assignment model. Step 3: The derivative ∂q w n /∂p w 1 (n ∈ N, w ∈ W) of the freight volume of transportation mode n to the disturbance parameter (railway freight price) under the condition of elastic demand is obtained by using the sensitivity analysis method, and the linear approximate expression of the reflection function is obtained according to Equations (35) to (37).…”