The shifting bottleneck procedure for job shop scheduling
Management Science
Heuristic Techniques for Single Line Train Scheduling
Journal of Heuristics
Rollout Algorithms for Combinatorial Optimization
Journal of Heuristics
Modeling Train Delays in Urban Networks
Transportation Science
Metaheuristics for minimizing the makespan of the dynamic shop scheduling problem
Advances in Engineering Software
A fast tabu search algorithm for the group shop scheduling problem
Advances in Engineering Software
A demand-responsive decision support system for coal transportation
Decision Support Systems
SIMARAIL: simulation based optimization software for scheduling railway network
Proceedings of the Winter Simulation Conference
Computers and Industrial Engineering
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In this paper, the train scheduling problem is modelled as a blocking parallel-machine job shop scheduling (BPMJSS) problem. In the model, trains, single-track sections and multiple-track sections, respectively, are synonymous with jobs, single machines and parallel machines, and an operation is regarded as the movement/traversal of a train across a section. Due to the lack of buffer space, the real-life case should consider blocking or hold-while-wait constraints, which means that a track section cannot release and must hold the train until next section on the routing becomes available. Based on literature review and our analysis, it is very hard to find a feasible complete schedule directly for BPMJSS problems. Firstly, a parallel-machine job-shop-scheduling (PMJSS) problem is solved by an improved shifting bottleneck procedure (SBP) algorithm without considering blocking conditions. Inspired by the proposed SBP algorithm, feasibility satisfaction procedure (FSP) algorithm is developed to solve and analyse the BPMJSS problem, by an alternative graph model that is an extension of the classical disjunctive graph models. The proposed algorithms have been implemented and validated using real-world data from Queensland Rail. Sensitivity analysis has been applied by considering train length, upgrading track sections, increasing train speed and changing bottleneck sections. The outcomes show that the proposed methodology would be a very useful tool for the real-life train scheduling problems.