A multi-objective optimization model to sustainable closed-loop solar photovoltaic supply chain network design: A case study in Iran

Along with the increasing rate of using renewable energies, following the finite amount of fossil fuel resources, and the associated pollution of these non-renewable energies, photovoltaic systems have recently achieved widespread acceptance to harness solar energy in the last decades. Since photovoltaic systems have a limited lifespan and cannot be used after a while, it seems imperative to pay attention to recycling and sustainability in the supply chain network design of these systems. In this respect, this paper first reviews the photovoltaic systems literature systematically. Thereinafter, a multi-objective, mixed-integer non-linear optimization model is deployed to design a photovoltaic supply chain network addressing the system's associated costs, environmental impacts, and social values. The concerned model also considers a reverse flow in addition to the typical forward flow in the proposed supply chain for special environmental and social issues. Likewise, to optimize the presented multi-objective model, the augmented epsilon-constraint method is employed, being capable of warranting the Pareto optimal solutions. Eventually, the model's efficiency is illustrated by discussing a real-world case in Iran, through which prominent managerial results are acquired.

Automated summary

With the rise of renewable energies, photovoltaic systems have gained widespread acceptance in recent decades for harnessing solar energy. This paper systematically reviews literature on photovoltaic systems and proposes a multi-objective, mixed-integer non-linear optimization model to design a photovoltaic supply chain network considering costs, environmental impacts, and social values. The model accounts for reverse flow and uses the augmented epsilon-constraint method to ensure Pareto optimal solutions, as demonstrated by a real-world case study in Iran.