Optimal multi-class rescheduling of railway traffic (original) (raw)
Related papers
2022
The railway timetables are designed in an optimal manner to maximize the capacity usage of the infrastructure concerning different objectives besides avoiding conflicts. The realtime railway traffic management problem occurs when the preplanned timetable cannot be fulfilled due to various disturbances; therefore, the trains must be rerouted, reordered, and rescheduled. Optimizing the real-time railway traffic management aims to resolve the conflicts minimizing the delay propagation or even the energy consumption. In this paper, the existing mixedinteger linear programming optimization models are extended considering a safety-relevant issue of railway traffic management, the overlaps. However, solving the resulting model can be time-consuming in complex control areas and traffic situations involving many trains. Therefore, we propose different runtime efficient multi-stage heuristic models by decomposing the original problem. The impact of the model decomposition is investigated mathematically and experimentally in different rail networks and various simulated traffic scenarios concerning the objective value and the computational demand of the optimization. Besides providing a more realistic solution for the traffic management problem, the proposed multi-stage models significantly decrease the optimization runtime.
Priority based technique for rescheduling trains
Journal of Fundamental and Applied Sciences, 2018
This paper presents a novel approach to solve a railway rescheduling problem using a Mixed Integer Goal Programming (MIGP) model rescheduling timetable based on train priorities whenever a service disruption occurs. The objectives are to minimize the total delay time of all trains in the rail line and maximize the service reliability. The experiments were done on Malaysian double track railway system and the model was solved using a heuristics approach great influence on the total delay time and service reliability. This r more advanced and practical model as it is able to produce the provisional timetable in short computing time and the solution generated satisfies all the restrictions posed by the rail operator.
Reducing the time needed to solve the global rescheduling problem for railway networks
16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013), 2013
In this paper a method is introduced to reduce the computation time needed to solve the global rescheduling problem for railway networks. The railway network is modeled as a switching max-plus-linear model. This model is used to determine the constraints of the rescheduling problem. The rescheduling problem is described as a Mixed Integer Linear Programming (MILP) problem. The dispatching actions in this implementation are limited to changing the order of the trains and breaking connections at stations. These dispatching actions are most effective for smaller delays. It is therefore assumed that the delays are less than some maximum value. The proposed reduction method determines which (combinations of) control inputs will never be used if the delays are below this maximum value and removes them, as well as the constraints associated to them, resulting in a smaller model. Using the reduced model in the MILP problem significantly decreases the time needed to solve the MILP problem while still yielding the optimal solution for the original MILP problem.
Optimization Based High-Speed Railway Train Rescheduling with Speed Restriction
Discrete Dynamics in Nature and Society, 2014
A decision support framework with four components is proposed for high-speed railway timetable rescheduling in case of speed restriction. The first module provides the speed restriction information. The capacity evaluation module is used to evaluate whether the capacity can fulfill the demand before rescheduling timetable based on deduction factor method. The bilayer rescheduling module is the key of the decision support framework. In the bilayer rescheduling module, the upper-layer objective is to make an optimal rerouting plan with selected rerouting actions. Given a specific rerouting plan, the lower-layer focuses on minimizing the total delay as well as the number of seriously impacted trains. The result assessment module is designed to invoke the rescheduling model iteratively with different settings. There are three prominent features of the framework, such as realized interaction with dispatchers, emphasized passengers’ satisfaction, and reduced computation complexity with a ...
Railway dynamic traffic management: Application of a train rescheduling system reducing delays
11th IFAC Symposium on Control in Transportation Systems, 2006, 2006
The paper applies principles of dynamic traffic management to solve the train re-scheduling problem faced by railway infrastructure managers during operations. When train operations are perturbed conflicts arise with respect to the scheduled train paths. A detailed mathematical formulation and dispatching algorithms are adopted to re-compute a new timetable of feasible arrival and departure times. The system generates a conflict free schedule with admissible train dynamics and with observance of minimum safety headway distances. Computational experiments on a part of the Dutch rail network show that the adopted rescheduling support system provides better solutions when compared to simple dispatching rules.
Optimized Train Dispatching and Rescheduling During a Disruption in a Bottleneck Section
Research Square (Research Square), 2022
Railway transportation is nowadays becoming one of the most preferred mode of transport due to its safety, capacity and reliability; the capital cost for the construction of the railway infrastructure is however very high and is characterized by high rigidity as the track layout is fixed; therefore there is need to optimally use the available infrastructure. Minor delays arising from a simple disruptions or even a single train failure can have massive impacts in terms of overall delays for subsequent trains using the track facility if not solved amicably. Disruptions can be attributed to power outages, mechanical failures, derailments, accidents or even environmental factors. In a case of multiple uncertain perturbations happening in a busy complex railway network, where there are many trains requesting to use the available track resources concurrently, there will be massive delays which has a lot of negative operational and economic implications as well as passengers' dissatisfaction. A mathematical model that is; a mixed-integer linear programming formulation is modelled to minimize total time delays in case of a set of multiple disruptions occurring on a busy track section i.e. bottleneck section, the model is formulated with consideration of sets of constraints factoring in feasible routes and safety margins and other operational dynamics such as dwell times to achieve optimal use of the available infrastructure. A number of numerical experiments based on arbitrary data and real network data are carried out to verify the effectiveness and efficiency of the proposed model. Performance of the designed model is evaluated and results are validated, the results obtained shows that the model offers an efficient rescheduled trains operation plan during disruptions, furthermore the performance of Fmincon solver and genetic algorithms (GA) are compared and their robustness evaluated, GA shows better performance during multiple disruption scenario.
A Constraint-Based Scheduling Model for Optimal Train Dispatching
2010 Joint Rail Conference, Volume 2, 2010
Railway networks are faced to an increase demand of new services. This situation leads to train schedules close to the maximum capacity of the infrastructure. As the extension of the infrastructure is too expensive, an alternative solution is to improve traffic management in congested areas. In heavy traffic areas of rail networks, conflicts and subsequent train delays can cause considerable chain reactions during operations. A disturbance can quickly lead to many other delays called secondary delays or knock-on delays.
A Survey on Problem Models and Solution Approaches to Rescheduling in Railway Networks
IEEE Transactions on Intelligent Transportation Systems, 2015
Rescheduling in railway networks is a challenging problem in both practice and theory. It requires good quality solutions in reasonable computation time to resolve unexpected situations, involving different problem scales, railway network infrastructures, objectives, and constraints. This paper presents a comprehensive survey on different problem models for rescheduling in railway networks by a clear classification. Some frequently used models are described in detail through reviewing their variables and constraints. This paper also focuses on the solution approaches proposed in the literature. The main ideas of the solution approaches with the objectives are described. Based on our review results, the analysis of the problem models used in various problem types and the solution approaches used in different problem models are presented. Conclusion and suggestions for further research to rescheduling in railway networks are drawn toward the end of the paper.
Multi-Strategy Based Train Re-Scheduling During Railway Traffic Disturbances
Disruptions and delays in railway traffic networks due to different types of disturbances is a frequent problem in many countries. When disruptions occur, the train traffic dispatchers may need to re-schedule the traffic and this is often a very demanding and complicated task. To support the train traffic dispatchers, we propose to use a parallelized multi-strategy based greedy algorithm. This paper presents three different parallelization approaches: (i) Single Strategy with a Partitioned List (i.e. the parallel processes originate from different starting points), (ii) Multiple Strategies with a Non-Partitioned List, and (iii) Multiple Strategies with a Partitioned List. We present an evaluation for a busy part of the Swedish railway network based on performance metrics such as the sum of all train delays at their final destinations and the number of delayed trains. The results show that parallelization helps to improve the solution quality. The parallel approach (iii) that combines all re-scheduling strategies with a partitioned list performs best among the three parallel approaches when minimizing the total final delay. The main conclusion is that the multi-strategy based parallel approach significantly improves the solution for 11 out of 20 disturbance scenarios, as compared to the sequential re-scheduling algorithm. The approach also provides an increased stability since it always delivers a feasible solution in short time.