Supply chain design of sustainable photovoltaic systems considering robust-fuzzy pricing and optimization

Abstract

Nowadays, the growing need for energy has led to an increasing use of fossil fuels, the issue leading to the devastating environmental effects, including global warming. Thus, the requirement of renewable technologies, particularly photovoltaic systems under such conditions is felt more than ever, which would result in reducing the environmental pollution. As a result, in the present research, a model is proposed for sustainable photovoltaic supply chain management. The considered innovations encompass pricing decisions using the Stackelberg model, considering the quality for return products, and fuzzy uncertainty. The question objectives are minimizing the photovoltaic supply chain’s costs, minimizing the adverse environmental effects, and managing social responsibility in the supply chain. The proposed model or using multi-objective weed algorithm and robust optimization approaches have been solved and the results suggest that as the demand increases, the environmental effects increase in both scenarios. Besides, the environmental effects of a boom scenario outweigh the costs of the bust scenario. Also, as the production costs increase, the environmental effects in both scenarios get down. Also, the boom scenario induced environmental effects outweigh the costs of a bust scenario. For instance, by the production cost increase up to 20%, the photovoltaic chain costs in the boom and bust scenario correspond to 86712 and 72912, respectively. Conversely, rising production costs lead to a decline in environmental impacts, and the boom scenario exhibits greater environmental effects compared to the bust scenario. Additionally, higher demand correlates with increased environmental effects for both scenarios, with the boom scenario consistently surpassing the environmental impacts of the bust scenario.