The growing demand for energy and emerging environmental concerns are making it necessary to look for more sustainable alternatives. To address the limitations of first-generation biofuels and reduce dependence on fossil fuels, this study focuses on second-generation bioethanol sourced from non-edible pomegranate waste. This study develops and analyses a supply chain optimization model for the sustainable production of biofuel from pomegranate waste and solves it using a genetic algorithm. The framework assesses key supply chain elements, including collection centres for pomegranate waste, processing plants, bio-refineries for conversion and distribution centres for final bioethanol. The primary objective of the optimization is to reduce the total cost of the biofuel production system and to maximize positive environmental impact through waste valorization. A numerical example validates the framework, and a sensitivity analysis further evaluates the economic viability of the supply chain under fluctuating market conditions, such as variations in the purchasing cost of waste, the production cost of bioethanol and the opening cost of plants. Biofuel production supports the Sustainable Development Goals (SDG-12 and -13) by transforming waste into renewable energy. This study aims to address gaps in biofuel research by focusing on the underutilized area of pomegranate-based biofuel through an integrated supply chain optimization framework. The findings offer practical values for researchers working on renewable energy solutions, policymakers and business leaders.
Saini et al. (Tue,) studied this question.