Sustainable biodiesel supply chain model based on waste animal fat with subsidy and advertisement

Abstract

The need for sustainable energy generation has grown in response to ascending levels of green house gases emissions and soaring energy demand. Biofuel is viewed as a viable alternative to non-renewable energy sources for energy generation. Animal fat, waste cooking oil, and vegetable oil are all examples of biomass that can be utilized to make biodiesel. In the midst of these sources’ animal fat is an acceptable choice due to its cheap cost and convenience of availability. The multi-objective mathematical optimization model is created to plan a sustainable supply chain for biodiesel made from waste animal fat. The proposed model minimizes the biodiesel supply chain cost, furthermore, minimizing the environmental impact while maximizing social impact. The demand for biodiesel is depending on advertisement costs and subsidies provided by the government. The advertisements promote biodiesel as an alternative to fossil fuels, and the government gives a subsidy for the collection of waste animal fat. The improved “augmented ϵ-constraint approach” is used to solve the proposed model. The multiple supply points for beef, mutton, and chicken fat, multi-collection and rendering plants, multiple biorefineries, and biodiesel depositories are designed. A numerical example is analyzed, and the consequences of a numerical experiment uncover that the transportation cost is 51.34% and installation cost of biodiesel production facilities accounts for 21.26% of the total cost, and the environmental installation impact of biodiesel production facilities accounts for 99.94% of total environmental impact. In the transportation sector, the heterogeneous fleet of trucks is employed to supply materials in the entire supply chain by which environmental transportation impacts account for 0.0005% of total environmental impacts. The social impact is examined by the social impact assessment method focused on life cycle assessment which is 1.363% for this model. The designed model can be appropriate to policymakers and investors engaged in the biodiesel industry.