Open AccessLINEAR PROGRAMMING MODEL FOR THE OPTIMIZATION OF THE BIODIESEL SUPPLY CHAIN IN THE MINDANAO ISLAND OF THE PHILIPPINES
Author(s) -
Yra Mae C. Camacho,
Kristin Joy Davila,
Ysabela Angela V. Flores,
Julie Anne D. del Rosario
Publication year - 2022
Publication title -
asean engineering journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.135
H-Index - 3
ISSN - 2586-9159
DOI - 10.11113/aej.v12.16498
Subject(s) - biodiesel , biofuel , carbon footprint , supply chain , linear programming , fossil fuel , integer programming , supply chain optimization , environmental science , environmental economics , business , waste management , computer science , engineering , greenhouse gas , supply chain management , economics , chemistry , marketing , ecology , biochemistry , algorithm , catalysis , biology
Biofuels are known to have several advantages over fossil fuels including, but not limited to, high abundance of resources, negligible SOx emissions, lower NOx emissions, and more environment-friendly processes. In the Philippines, the biofuels industry is anchored onto the Biofuels Act of 2006 which mandates the use of biofuels made from indigenous sources such as coconut. Despite this, biodiesel is still less preferred by consumers over conventional fuel due to its high cost. This can be attributed to high production costs of biodiesel, wherein 18-28% is credited to transportation of products. This work proposes a linear programming model to reduce the overall cost of biodiesel by minimizing the transportation cost in the Philippine biodiesel supply chain, using the Mindanao cluster as case study. Multiple scenarios were done to gauge the impact of varying the supply allocation and biodiesel blend on the supply chain. The optimal supply allocation, transportation cost, and carbon footprint of each scenario were determined. A new facility locator feature was also added as an extension of the program. Results also showed high reproducibility using easily accessible programming tools such as Microsoft Excel and Python.