Modeling and Heuristically Solving Group Train Operation Scheduling for Heavy-Haul Railway Transportation

Abstract

In light of the improvements to the capacity and timeliness of heavy-haul railway transportation that can be organized through group trains originating at a technical station, we address a group train operation scheduling problem with freight demand importance via a newly proposed mixed integer programming model and a simulated annealing algorithm. The optimization objective of the mixed integer programming model is to minimize the weighted sum of the transportation cost and the total cargo travel time under the condition of matching freight supply and demand within the optimization period. The main constraints are extracted from the supply and demand relations, the cargo delivery time commitment, the maintenance time, and the number of locomotives. A simulated annealing algorithm was constructed to generate the grouping scheme, the stopping scheme and the running schedule of group trains. A numerical experiment based on a real heavy-haul railway configuration was employed to verify the efficacy of the proposed model and heuristics algorithm. The results show that the proposed methodology can achieve high-quality solutions. The case results reveal that the freight volume increased by 2.03%, the departure cost decreased by CNY 337,000, the transportation cost which results from the difference in the supply and demand matching increased by CNY 27,764, and the total cargo travel time decreased by 40.9%, indicating that group train operation can create benefits for both railway enterprises and customers.

Optimizing Mixed Group Train Operation for Heavy-Haul Railway Transportation: A Case Study in China

“…Xu [13] proposed an optimization model for a Y-type routing scheme that could ensure a relative balance between the load factors on various sections of the line while reducing the travel costs to passengers and the operating costs to enterprises. Chen et al [3] proposed a mixed integer programming model aiming at transportation cost and travel time, and solved the fixed group train operation plan.…”

“…Freight transportation demand has several elements, including the initial station, the terminal station, the distance between the two stations, the committed arrival time, the theoretical demand, the actual supply and the actual gain. Since the operation plan for the heavy-haul train studied here is based on the background of organizing through trains at the initial technical station, we only consider the initial station and the terminal station for each freight transportation demand [3]. In our research, we assume a heavy-haul railway line with 1 + K stations.…”

“…Equation (2) shows the advantage of GTO in shortening the train interval, which is shown in more detail in Figure 6. For TO, the goal can be shown as Equation (3), where m represents the number of trains:…”

“…On the northern line of BaoShen Railway, the verification of operational experiments in heavy-haul trains has been carried out using group control technology. From the perspective of the transportation organization, this kind of train operation organization with group control technology is called GTO [3]. It can be seen from Figure 1 that the tracking interval for GTO is shorter than in TO (L unit means the interval distance between the adjacent trains in GTO and L traditional represents the interval distance between the adjacent trains in TO).…”

Model of Multi Criteria Decision-Making for Selection of Transportation Alternatives on the Base of Transport Needs Hierarchy Framework and Application of Petri Net

“…The paper [9] discusses research to optimize the scheduling of production orders in packaging using mixed integer linear programming and constraint programming models. It extends the flexible flow shop problem with precedence, parallel machines, sequencedependent setups, and availability constraints to minimize total tardiness.…”