Optimization of a macro-algae-based biodiesel supply chain: a multi-objective approach

Abstract The rising consumption of fossil fuels and the emission of greenhouse gases have made sustainable energy generation an absolute necessity. With its ability to be produced from a variety of biomass sources, including non-edible ones like macro-algae, animal fat and used cooking oil, biofuels have the potential to provide a sustainable energy alternative to non-renewable sources. Macro-algae serves as a cost-effective and accessible solution for energy generation. Accelerated biodiesel supply chain development is essential to support large-scale sustainable production. This research focuses on designing an optimized and sustainable supply chain for third-generation biodiesel production from macro-algae. The main contribution lies in developing a multi-objective optimization model that minimizes supply chain costs and environmental impacts while addressing critical factors such as transportation logistics, facility placement and the impact of advertising on biodiesel demand. The proposed strategy effectively reduces supply chain costs and environmental impacts. Advertising promotes biodiesel as an alternative to fossil fuels, thereby influencing its demand. The proposed multi-objective optimization model is implemented using the Genetic Algorithm. Three macro-algae species (Ulva fasciata, Cystoseira indica and Gracilaria corticata) are strategically integrated into an extensive network of bio-refineries, biodiesel depots, multi-extraction centres and diverse supply sources. The findings highlight substantial costs associated with biofuel supply chain installation, with production facilities accounting for 61.6% of the biodiesel setup costs. Biofuel supply chain installation contributes 69.8% of the total environmental impact. A numerical example and sensitivity analysis of essential factors are conducted to assess the model’s practicality and validity.