Optimization of Bioethanol Supply Chain from Starch-Based Household FOOD Waste: A Cost Minimization Modelling Framework

A sustainable cost optimization framework for the bioethanol supply chain is developed, using household food waste as a renewable feedstock. Unlike previous studies that mainly focus on agricultural residues, algae, or industrial biomass, this research addresses the specific logistical and economic challenges associated with household food waste, including decentralized generation, perishability, transportation complexity, and variable supply patterns. The proposed mathematical model incorporates key supply chain costs, including waste purchasing, handling, transportation, storage, processing, and facility installation, to minimize the total operational cost of the supply chain network. A genetic algorithm-based optimization approach is applied to determine the optimal configuration of collection centres, processing facilities, and distribution hubs subject to operational and capacity constraints. The numerical results indicate that the proposed framework improves supply chain efficiency while reducing overall system cost. The findings suggest that household food waste can serve as a sustainable and economically viable resource for decentralized bioethanol production and environmentally sustainable urban waste management.