Evaluating the Applicability of Advanced Techniques for Practical Real-time Train Scheduling

AbstractThis paper reports on the practical applicability of published techniques for real-time train scheduling. The final goal is the development of an advanced decision support system for supporting dispatchers’ work and for guiding them toward near-optimal real-time re-timing, re-ordering and re-routing decisions. The paper focuses on the optimization system AGLIBRARY that manages trains at the microscopic level of block sections and block signals and at a precision of seconds. The system outcome is a detailed conflict-free train schedule, being able to avoid deadlocks and to minimize train delays. Experiments on a British railway nearby London demonstrate that AGLIBRARY can quickly compute near-optimal solutions

Evaluation of VaR and CVaR for the makespan in interval valued blocking job shops

3noreservedThe paper deals with the job shop scheduling problem with complex blocking constraints (BJSS) under uncertainties. It proposes a method for the evaluation of the risk that the makespan of a deterministic feasible schedule assumes worse extreme values, considering uncertain activity durations represented by intervals. An interval-valued network approach is proposed to model the feasible solutions characterized by uncertain values for jobs’ releases, processing and setup times. The study assumes the Value-at-Risk (VaR) and the Conditional Value-at-Risk (CVaR) as risk measures for the makespan of the feasible solutions, and addresses both modeling and computational issues. They include the implementation and test of a network-based model used with an innovative algorithm for the first time applied to complex BJSS problems to provide an accurate, rapid and viable computation of both risk indices. The impact of different sources of uncertainty (including setups, releases and processing times) on the overall performance of the proposed approach are analyzed. The results of a wide experimental campaign show that the method, for both the computational time and the quality of the evaluations, has broad applicability. It can support the decision-makers for a wide range of practical scheduling cases taking into account their risk sensibility.mixedMeloni C.; Pranzo M.; Sama M.Meloni, C.; Pranzo, M.; Sama, M

Expected Shortfall for the Makespan in Activity Networks with Fuzzy Durations

The paper deals with the evaluation of the Expected Shortfall or the Conditional Value-at-Risk for the makespan in scheduling problems represented as temporal activity networks where we assume that only a type-1 fuzzy representation for the activity integer valued durations is known to the scheduler. More precisely, we address the evaluation of the Expected Shortfall associated to a feasible schedule, and we extend the approach recently proposed for the case of interval valued durations. We develop and analyze a suitable computational method to obtain the fuzzy evaluation of the Expected Shortfall of the makespan of a given schedule. The proposed method enables to use the Expected Shortfall as quality criterion for wide classes of scheduling approaches considering risk-aversion in different practical contexts when only a fuzzy representation of activity durations is known

Coordination of scheduling decisions in the management of airport airspace and taxiway operations

This paper addresses the real-time problem of coordinating aircraft ground and air operations in an airport area. At a congested airport, airborne decisions are related to take-off and landing operations, while ground (taxiway) decisions consist of scheduling aircraft movements between the gates and the runways. Since the runways are the initial/terminal points of both decisions, coordinated actions have a great potential to improve the overall performance. However, in the traffic control practice the different decisions are taken by different controllers, at least in large airports. Weak coordination may result in long queues at the runways, with increasing aircraft delays and energy consumption. This paper investigates models, methods and policies for improving the coordination between taxiway scheduling and airborne scheduling. The performance of a solution is measured in terms of delay and travel time, the latter being related to the energy consumption of an aircraft. A microscopic mathematical formulation is adopted to achieve reliable solutions. Exact and heuristic methods have been analysed in combination with the different policies, based on practical-size instances from Amsterdam Schiphol airport, in the Netherlands. Computational experience shows that good quality solutions can be found within limited time, compatible with real-time operations.ISSN:2352-146

A multi-criteria decision support methodology for real-time train scheduling

This work addresses the real-time optimization of train scheduling decisions at a complex railway network during congested traffic situations. The problem of effectively managing train operations is particularly challenging, since it is necessary to incorporate the safety regulations into the optimization model and to consider key performance indicators. This paper deals with the development of a multi-criteria decision support methodology to help dispatchers in taking more informed decisions when dealing with real-time disturbances. Optimal train scheduling solutions are computed with high level precision in the modeling of the safety regulations and with consideration of state-of-the-art performance indicators. Mixed-integer linear programming formulations are proposed and solved via a commercial solver. For each problem instance, an iterative method is proposed to establish an efficient-inefficient classification of the best solutions provided by the formulations via a well-established non-parametric benchmarking technique: data envelopment analysis. Based on this classification, inefficient formulations are improved by the generation of additional linear constraints. Computational experiments are performed for practical-size instances from a Dutch railway network with mixed traffic and several disturbances. The method converges after a limited number of iterations, and returns a set of efficient solutions and the relative formulations

Rescheduling Railway Traffic Taking into Account Minimization of Passengers’ Discomfort

ISSN:0302-9743ISSN:1611-334

On the tactical and operational train routing selection problem

In the real-time railway traffic management problem, the number of alternative routings available to each train strongly affects the size of the problem and the time required to optimally solve it. The train routing selection problem identifies a suitable subset of alternative routings to be used for each train in the real-time railway traffic management. This paper analyzes the impact of solving the train routing selection problem at different levels. The problem can be solved at tactical level right after the timetabling process, using historical traffic data and with abundant computation time. In this case the problem constitutes an integration step between the timetabling and the real-time traffic management. Alternatively, the problem can be solved at operational level right before the real-time railway traffic management problem solution, using up to date traffic perturbation and a real-time time limit of computation. Experiments are performed on two French test cases, the line around Rouen and the Lille station area, for several disturbed and disrupted scenarios. The results show that the best approach depends on the type of traffic disturbance tackled

Terminal Control Area Aircraft Scheduling and Trajectory Optimization Approaches

Aviation authorities are seeking optimization methods to better use the available infrastructure and better manage aircraft movements. This paper deals with the realtime scheduling of take-off and landing aircraft at a busy terminal control area and with the optimization of aircraft trajectories during the landing procedures. The first problem aims to reduce the propagation of delays, while the second problem aims to either minimize the travel time or reduce the fuel consumption. Both problems are particularly complex, since the first one is NP-hard while the second one is nonlinear and a combined solution needs to be computed in a short-time during operations. This paper proposes a framework for the lexicographic optimization of the two problems. Computational experiments are performed for the Milano Malpensa airport and show the existing gaps between the performance indicators of the two problems when different lexicographic optimization approaches are considered