## 2 Literature Review
[PERSON] [13] combined qualitative and quantitative analyses, combining the hierarchical analysis method (AHP), the data envelopment analysis method (DEA), and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). This approach harmonizes conflicting criteria to select the most appropriate alternatives and provide multimodal transportation routes. The effectiveness of this method was verified through real-world transportation route selection cases. Some studies focus on coal supply chain networks, addressing multisupplier and multi-power-plant transfer optimization problems primarily by constructing mixed-integer programming models to determine optimal path selection and flow allocation. [PERSON] [14] explored the issue of coal transportation network reuse at the New England port, firstly constructing an integer planning model to minimize the total cost. This model was later extended to a multiobjective optimization model, balancing the cost and efficiency of coal transportation, and validated through real case studies. The optimization model of multiobjective planning was extended to consider the optimization model of multiobjective planning, and a proposal for balancing the cost and efficiency of coal transportation was made through a real case study [9]. [PERSON] [15] examined the practical problem of transporting coal from western Canada to power stations in eastern Canada, using a simulation model to evaluate potential paths. This research provides a reference for strategic decision making regarding coal transportation, though it requires a substantial database to reflect real-world conditions accurately. [PERSON] [16] applied a multiperiod generalized network flow model to optimize the overall efficiency of energy supply schemes, considering the substitution effects of coal and natural gas, and analyzed the economic efficiency of energy movement from coal and natural gas suppliers to power load centers, which enriched the perspective of analyzing the energy problem. [PERSON] [17] investigated the coal transportation path selection problem involving multiple suppliers and types of coal, establishing a mixed-integer model for optimal path selection. [PERSON] studied the procurement and transportation problem of an electric utility company with multiple power plants and suppliers, considering procurement, transportation, and inventory cost. [PERSON]'s mixed-integer programming model aimed to minimize total costs, effectively optimizing transportation for multiple suppliers and demand points. [PERSON] [18] focused on determining the shortest path of a coal and power transportation network by connecting the coal source and coal consumption places to form a minimum spanning tree solved using a shortest-path routing algorithm. Various studies have been conducted to analyze and improve the route optimization of coal multimodal transport, considering factors such as coal transportation direction and source locations in transfer areas [19]. The impact of air pollution caused by dust emissions during coal storage, transfer, and transportation has also been a significant concern, prompting the application of robust optimization techniques in designing air-quality monitoring networks [20]. Furthermore, models utilizing genetic algorithms have been proposed for optimizing coal procurement and transportation decisions, particularly for thermal power plants [21]. Moreover, research has been conducted on optimizing coal truck flow in open-pit mines, emphasizing the importance of efficient coal mining, transportation, and processing operations [22]. Overall, the optimization of coal transfer and transportation processes is essential for improving efficiency, reducing costs, and minimizing environmental impacts in the coal industry. Most current studies on coal transfer optimization focus on the selection of transport paths and flow distribution, including the selection of transport modes.