Palm Oil Biomass Supply Chain Multi-Objective Two-Echelon Location-Routing Optimization

Malaysia generates substantial agricultural residues annually, endowing the country with significant biomass energy potential. Palm oil biomass stands out as a promising feedstock. However, its high humidity, bulkiness, low energy density, and dispersed resource locations (mills) pose challenges. A network that consisting collection facilities incorporating pretreatment operations as intermediaries between mills and biorefineries is a plausible solution. Nevertheless, the facility locations directly impact travel distance, overall expenses, and the nearby population. Moreover, vehicle routing during biomass collection influences transportation costs and carbon dioxide (CO2) emissions. Consequently, this research designs a model to address the location-routing intricacies within a two-echelon biomass supply chain. The model operates as a multi-objective optimization framework, encompassing three-dimensional sustainability assessment, quantified respectively as total cost minimization, CO2 emissions reduction, and minimization of the population affected. The research initially optimizes each objective function individually and subsequently advances to multi-objective optimization employing the weighted sum approach. While single-objective optimization yields optimal outcomes for each dimension, enhancements in one aspect may hinder performance in others. Nonetheless, the multi-objective optimization provides insight into the trade-offs among the sustainability objectives. The computational findings demonstrate the model could adapt the network configuration in alignment with distinct sustainability aspirations.