Analysis on line capacity usage for China high speed railway with optimization approach

The purpose for the analysis of capacity usage is to utilize the rail infrastructure in a more efficient and practical way. The practical and theoretical challenge of the rail capacity is its dynamics and uncertainty, which are common in China and elsewhere. Based on the capacity balance, a train service-demand intention set (TSDIS) at High-Speed Rail (HSR) line (t@l-TSDIS) is defined, which takes the number of trains, the average speed, the heterogeneity and the stability as the core elements for the capacity usage. For dynamics and uncertainty, we update the norm for capacity measure as the time needed to fulfill the task list t@l-TSDIS. Then we develop the objectives and constraints for the Mathematical Program for Line Capacity (MPLC), which aims at minimization of heterogeneity and running time as well as maximization of reliability. For solving MPLC, the Pareto Archived Evolutionary Strategy (PAES) and fuzzy logic penalty function are introduced. Furthermore we propose a rolling optimization tactic oriented by the practical problem, which combines the improved Pareto Archived Evolutionary Strategy (iPAES) with an interactive technique. In a case study, we apply the proposed ideas and methodology to Beijing-Shanghai HSR (BS-HSR) line much closer to the railway practice. By using the computer language C# to compile the Console program, Pareto optimized results for MPLC are achieved, including the standard and practical values for the heterogeneity indices, reliability indices and running time indices. We also discuss the sensitivity of the heterogeneity index. This research demonstrates that it is useful to analyze the line capacity usage for China HSR with the proposed optimization approach.