Research on Optimization of Hybrid Axial Radial Provincial Coal Logistics Network Considering Carbon Emissions

To address the complex structure, low efficiency, high costs, and excessive carbon emissions in provincial coal logistics networks, this study proposes a hybrid hub-and-spoke network optimization method integrating economic and environmental objectives. We develop a bi-objective nonlinear programming model that systematically integrates hub constructioncosts, transportation costs, and carbon emission factors from transfer operations. An enhanced NSGA-II algorithm featuringdynamic crossover probability and hill-climbing-based local search strategies is designed to improve convergence speed andsolution diversity. Empirical analysis of Shanxi Province's network (11 cities and 8 external nodes) demonstrates that whenscale effect coefficient θ=0.55 with 4 hubs, the hybrid network achieves 25.75% cost reduction and 58.75% emission reduction compared with direct transportation. Sensitivity analysis reveals nonlinear coupling between scale effects and hub quantity, confirming optimal configuration at θ=0.55 with 4 hubs for maximal economic-environmental benefits. This research validates that hub-intensive operations in hybrid networks can synergistically optimize scale economies and emission reduction, providing quantifiable decision support for low-carbon transformation of provincial coal logistics.