An Environmentally Sustainable Closed-Loop Supply Chain Network Design Under Uncertainty: Application of Optimization

Abstract

Newly, the rates of energy and material consumption to augment industrial production are substantially high, thus the environmentally sustainable industrial development has emerged as the main issue of either developed or developing countries. A novel approach to supply chain management is proposed to maintain economic growth along with environmentally friendly concerns for the design of the supply chain network. In this paper, a new green supply chain design approach has been suggested to maintain the financial virtue accompanying the environmental factors that required to be mitigated the negative effect of rapid industrial development on the environment. This approach has been suggested a multi-objective mathematical model minimizing the total costs and CO2 emissions for establishing an environmentally sustainable closed-loop supply chain. Two optimization methods are used namely Epsilon Constraint Method, and Genetic Algorithm Optimization Method. The results of the two mentioned methods have been compared and illustrated their effectiveness. The outcome of the analysis is approved to verify the accuracy of the proposed model to deal with financial and environmental issues concurrently.

Designing a new multi-echelon multi-period closed-loop supply chain network by forecasting demand using time series model: a genetic algorithm

“…For statistical analysis, we use the least significant difference method (LSD) to find significant differences (Chouhan et al 2021, Arani et al 2021, Dehdari Ebrahimi, et al 2017, Ahmed et al 2020. Figure 6 shows the output of the LSD method using the MINITAB statistical software.…”