Presenting a robust optimization model for the design of the green loop supply chain network in the power plant by taking into account the disruption in the supply chain

This paper focuses on modeling a sustainable electricity industry supply chain network under uncertainty. The aim of presenting this supply chain network is to meet customer demands for solar panels to generate clean energy.

A mixed-integer linear programming model, including facility location, supplier selection, optimal flow allocation, and determination of the optimal price of solar panels in the network, is considered. The sustainability objectives of the model include maximizing the profit of the supply chain network, minimizing greenhouse gas emissions, and maximizing reliability. A robust optimization method is also considered to control uncertain parameters, and precise and innovative techniques are used to solve the model.

The results of the model show that with an increase in network reliability, the current net value in the network decreases, and greenhouse gas emissions in the network increase. Additionally, the analysis of the results shows that with an increase in the network's uncertainty rate, the network's current net value and reliability decrease, and greenhouse gas emissions increase. Finally, the statistical test results also show that there was no significant difference between the averages of the number of practical solutions, the maximum spread, and the metric distance between the two algorithms, and only a significant difference exists between the solution times of the two algorithms. The results of the presented solution methods demonstrate their high efficiency in solving the sustainable electricity industry supply chain model.

Originality/Value:

 In the proposed model, essential decisions such as supplier selection, establishment of production centers, optimal product flow allocation, and pricing of solar panels are made. On the other hand, further analyses of 15 numerical examples show the high efficiency of the MOALO and MOWOA algorithms compared to the epsilon-constraint method.