Green Closed-Loop Supply Chain Network Design During the Coronavirus (COVID-19) Pandemic: a Case Study in the Iranian Automotive Industry

Abstract

This paper presents a new mathematical model of the green closed-loop supply chain network (GCLSCN) during the COVID-19 pandemic. The suggested model can explain the trade-offs between environmental (minimizing CO₂ emissions) and economic (minimizing total costs) aspects during the COVID-19 outbreak. Considering the guidelines for hygiene during the outbreak helps us design a new sustainable hygiene supply chain (SC). This model is sensitive to the cost structure. The cost includes two parts: the normal cost without considering the coronavirus pandemic and the cost with considering coronavirus. The economic novelty aspect of this paper is the hygiene costs. It includes disinfection and sanitizer costs, personal protective equipment (PPE) costs, COVID-19 tests, education, medicines, vaccines, and vaccination costs. This paper presents a multi-objective mixed-integer programming (MOMIP) problem for designing a GCLSCN during the pandemic. The optimization procedure uses the scalarization approach, namely the weighted sum method (WSM). The computational optimization process is conducted through Lingo software. Due to the recency of the COVID-19 pandemic, there are still many research gaps. Our contributions to this research are as follows: (i) designed a model of the green supply chain (GSC) and showed the better trade-offs between economic and environmental aspects during the COVID-19 pandemic and lockdowns, (ii) designed the hygiene supply chain, (iii) proposed the new indicators of economic aspects during the COVID-19 outbreak, and (iv) have found the positive (reducing CO₂ emissions) and negative (increase in costs) impacts of COVID-19 and lockdowns. Therefore, this study designed a new hygiene model to fill this gap for the COVID-19 condition disaster. The findings of the proposed network illustrate the SC has become greener during the COVID-19 pandemic. The total cost of the network was increased during the COVID-19 pandemic, but the lockdowns had direct positive effects on emissions and air quality.

Keywords: CO2 emissions; Lockdowns; Logistic network; Multi-objective optimization; Supply chain management; Weighted sum method.

Fig. 1

Change in the emission of CO₂ during the pandemic [8]

Fig. 2

The logistics networks between echelons are depicted

Fig. 3

An illustration of the Pareto solutions [80]

Fig. 4

Software output for economic and environment optimization values

Fig. 5

A closed-loop network in small dimensions displayed

Fig. 6

The comparison between economic and environmental performances of numerical examples based on the importance of economic factors

Fig. 7

The comparison between economic and environmental performances of numerical examples based on the importance of environmental factors

Fig. 8

Sensitivity analysis for different weights of environment and economic aspects

Fig. 9

a-i Relationship between gas emissions and COVID-19 [88]

Fig. 10

- Analysis of the relationship between total CO₂ emissions due to activities and COVID-19 [89]

Fig. 11

CO₂ emission in India during the COVID-19 pandemic [90]

Fig. 12

Change in activity during the COVID-19 pandemic [91, 92]

Fig. 13

Iran's average GHG emissions between March 21 and April 21, 2019 and 2020 [93]

Fig. 14

Sensitivity analysis of the economic objective value

Fig. 15

Sensitivity analysis of the environment objective value