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• Sustainable analysis of pellet supply chain from a sea haulage perspective using fuel cost model. • MLP-ANN embedded ATSP routing can mitigate emissions significantly. • The optimal ship’s capacity is identified using sensitivity analysis. Biomass pellet offers a potential alternative to partially supplant fossil fuels to accelerate the process of decarbonization. The substantial price difference between coal and wood pellets is a barrier to utilizing this alternative. This paper assesses the critical aspects of implementing this solution for the pellet supply chain (PSC). We propose a Multilayer Perceptron Artificial Neural Network (MLP-ANN) model for container ship fuel cost and Discrete Event Simulation (DES). The research provides a sustainable analysis of PSC from the economic and environmental dimensions. The effectiveness of the Asymmetric Traveling Salesman Problem (ATSP) routing algorithm embedded in MLP-ANN is further examined using DES. The result reveals that adopting the ATSP-MLP can cut total costs by approximately 5.5 %, 15.2 %, and 22.1 % for Suppliers 1, 2, and 3, respectively. The mitigations in carbon dioxide (CO 2 ) emissions are over 25.6 %, 28.2 %, and 52.6 % for Suppliers 1, 2, and 3. A sensitivity analysis is conducted to assist suppliers in identifying the optimal ship capacity for chartering and considering the variations of Key Performance Indicators (KPIs) by fuel price volatility. This study provides significant theoretical and practical insights for stakeholders to establish collaborative mechanisms for traditional PSC operators in developing countries, thereby leveraging economic benefits from routing solutions. The substantial elimination of costs and carbon emissions also motivates the shift from fossil fuels to biomass fuels for decarbonization.
Ta et al. (Sat,) studied this question.