A robust possibilistic programming approach toward animal fat-based biodiesel supply chain network design under uncertain environment

The fast depletion of fossil fuels and adverse environmental impact from combustion have triggered an urgent need for new, cleaner and sustainable energy resources. In the last few decades, biodiesel has been introduced as an alternative due to its advantages over fossil fuels, which include higher flash point, improved lubricity, and lower toxicity. However, high production cost of biodiesel is one of the major hindrances in making the commercial feasibility of biodiesel viable. Biodiesel can be obtained from various sources such as waste cooking oil, vegetable oil, animal fat, etc. Among these sources, animal fat which is a non-edible feedstock and currently being used in low-cost processes is one of the best options. To make the commercial feasibility of biodiesel viable, this research presents an animal fat-based bio-diesel supply chain network design optimization model. The suggested optimization model minimizes the cost of total biodiesel supply chain operations besides minimizing the carbon emissions during the involved operations. The complex and dynamic business environment of the biodiesel supply chain leads to a high degree of uncertainty, as a result, the effectiveness of strategic level decisions is compromised. To model this uncertainty, a solution methodology based on robust possibilistic programming (RPP) is employed. To show the applicability of the proposed model and solution methodology, numerical experiments and sensitivity analysis on a real case study is performed. Case results depict that RPP based solution methodology can achieve efficient solutions having a high degree of robustness. The experimental results also indicate that by investing almost 16% higher cost, the strategic and tactical level decisions of the proposed biodiesel supply chain model can be secured against the inherent uncertainty. It is also revealed that for the given case, logistics-related activities are almost 80% of the total supply chain cost, which if managed efficiently, can play a significant role in making the commercial feasibility of biodiesel doable. The proposed model and its findings can be efficiently utilized by the policymakers and investors in the animal fat-based biodiesel production sector. (C) 2020 Elsevier Ltd. All rights reserved.

Automated summary

This research proposes an animal fat-based bio-diesel supply chain network design optimization model to minimize the cost of total biodiesel supply chain operations and reduce carbon emissions. Through a real case study, it is found that the solution methodology based on robust possibilistic programming can achieve efficient solutions with high robustness. The study also highlights the significant role of managing logistics-related activities in reducing the overall supply chain cost and making the commercial feasibility of biodiesel feasible.