A variable neighbourhood search for fast train scheduling and routing during disturbed railway traffic situations

This paper focuses on the development of metaheuristic algorithms for the real-time traffic management problem of scheduling and routing trains in complex and busy railway networks. This key optimization problem can be formulated as a mixed integer linear program. However, since the problem is stron...

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Vydáno v:Computers & operations research Ročník 78; s. 480 - 499
Hlavní autoři: Samà, Marcella, D׳Ariano, Andrea, Corman, Francesco, Pacciarelli, Dario
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Elsevier Ltd 01.02.2017
Pergamon Press Inc
Témata:
Algorithms
Alternative graph
Branch-and-bound
Disjunctive programming
Neighborhoods
Optimization
Railway networks
Real time
Real-time railway traffic management
Studies
Tabu search
Train scheduling and routing
Trains
Variable neighbourhood search
Branch-and-bound
Tabu search
Disjunctive programming
Alternative graph
Variable neighbourhood search
Real-time railway traffic management
Train scheduling and routing
ISSN:0305-0548, 1873-765X, 0305-0548
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Shrnutí:This paper focuses on the development of metaheuristic algorithms for the real-time traffic management problem of scheduling and routing trains in complex and busy railway networks. This key optimization problem can be formulated as a mixed integer linear program. However, since the problem is strongly NP-hard, heuristic algorithms are typically adopted in practice to compute good quality solutions in a short computation time. This paper presents a number of algorithmic improvements implemented in the AGLIBRARY optimization solver in order to improve the possibility of finding good quality solutions quickly. The optimization solver manages trains at the microscopic level of block sections and at a precision of seconds. The solver outcome is a detailed conflict-free train schedule, being able to avoid deadlock situations and to minimize train delays. The proposed algorithmic framework starts from a good initial solution for the train scheduling problem with fixed routes, obtained via a truncated branch-and-bound algorithm. Variable neighbourhood search or tabu search algorithms are then applied to improve the solution by re-routing some trains. The neighbourhood of a solution is characterized by the set of candidate trains to be re-routed and the available routes. Computational experiments are performed on railway networks from different countries and various sources of disturbance. The new algorithms often outperform a state-of-the-art tabu search algorithm and a commercial solver in terms of reduced computation times and/or train delays. •Variable neighbourhood search algorithms are proposed for efficient railway traffic control.•New neighbourhood search strategies for real-time train re-routing are developed.•Practical railway test cases from various European countries are investigated.•The new algorithms compute good quality solutions in a short computation time.•The new algorithms often outperform a state-of-the-art tabu search algorithm.
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ISSN:0305-0548
1873-765X
0305-0548
DOI:10.1016/j.cor.2016.02.008