Editorial

摘要

This first issue of the second volume contains four articles on different topics ranging from rail freight network optimization, impact assessment of competition into rail passenger markets, performance comparison of different optimization methods to minimize delay costs, and stochastic modelling of delay propagation. The first article by Backaker & Tornquist Krasemann presents an optimization-based freight routing and scheduling policy to solve the rail freight trip generation problem. It is applied on real data from a network of 4 railway yards provided by the Swedish rail freight operator Green Cargo. The second article by Johnson & Nash examines the impact of introducing competition in the provision of rail passenger services by two alternative ways - open access and franchising by means of competitive tenders. They found franchising services have provided better services at lower costs than previously the case, especially for unprofitable regional lines. The third article by Fan, Roberts and Weston evaluates the performance of a large number of existing optimization methods for rescheduling 3 different train types at a simple junction area of two lines merging and diverging under 4 different delay scenarios. The 8 algorithms tested comprise brute force numerical computation, first-come-first-served, Tabu search, simulated annealing, genetic algorithms, ant colony optimisation, dynamic programming, and decision tree based elimination. Ant colony optimisation and genetic algorithms performed well compared to first-come-first-served. The fourth article by Biiker & Seybold proposes the modelling of delay propagation in large railway networks by means of an activity graph, whose nodes represent activities as train arrivals and departures that are connected by attributed arcs. The propagation of delays is modelled by means of random variables. Four approaches for calibration of the graph model are described depending on the availability of empirical distributions of explicit primary, knock-on and total delays. The analytical model has been applied successfully for the estimation of delay propagation on the rail network of the Swiss Railways SBB.