Green logistics optimization for coal supply in a power plant connecting maritime port

This study addresses the coal transportation and flow distribution challenges within a "port-before-plant" type thermal power plant, with a strong emphasis on green logistics principles. Despite significant advancements in clean energy, coal remains a dominant energy source in China, necessitating optimization in its usage and management to mitigate environmental impacts. This paper introduces an integrated optimization model grounded in green logistics and employs an Improved Particle Swarm Optimization (IPSO) algorithm to efficiently manage the coal supply chain from unloading at ports to loading into generators. The model incorporates new parameters and constraints that not only reflect the operational realities of coal logistics but also emphasize minimizing carbon emissions and energy consumption. Numerical experiments demonstrate the algorithm's superior performance compared to traditional solvers like Gurobi, particularly in handling large-scale instances. Sensitivity analysis reveals the importance of prioritizing efficient and environmentally sustainable unloading and loading equipment, suggesting strategies for optimizing green coal transportation routes. Overall, this research provides valuable insights for policymakers and industry operators to enhance operational efficiency while ensuring environmental sustainability through the implementation of green logistics.