An intelligent simulation platform for train traffic control under disturbance. (3rd July 2019)

• Record Type: Journal Article
• Authors: Shakibayifar, Masoud; Hassannayebi, Erfan; Mirzahossein, Hamid; Taghikhah, Firouzeh; Jafarpur, Amir
• Is Part Of: International journal of modelling & simulation. Volume 39:Number 3(2019)
• Page Start: 135
• Page End: 156
• Publication Date: 2019-07-03
• Subjects: Train rescheduling -- multi-objective optimization -- discrete-event simulation -- disturbance management; Mathematical models -- Periodicals; Simulation methods -- Periodicals; Mathematical models; Simulation methods; Periodicals; 003.3
• DOI: 10.1080/02286203.2018.1488110
• Languages: English
• ISSNs: 0228-6203

Abstract

ABSTRACT: Railway disturbance management is inherently a multi-objective optimization problem that concerns both the operators' cost and passenger's service level. This study proposes a multi-objective simulation-based optimization framework to effectively manage the train conflicts after the occurrences of a disturbance caused by a temporary line blockage. The simulation model enhanced with a dynamic priority dispatching rule in order to speed up the optimization procedure. A multi-objective variable neighborhood search meta-heuristic is proposed to solve the train rescheduling model. The obtained Pareto optimal solutions for disturbance management model support the decision maker to find a trade-off between both user and operator viewpoints. The proposed approach has been validated on a set of disruption scenarios covering a large part of the Iranian rail network. The computational results prove that the proposed model can generate good-quality timetables with the minimum passenger delay and deviation from the initial timetable. The outcomes indicate that the developed simulation-based optimization approach has substantial advantages in producing practical solution quickly when compared to currently accepted solutions. Abbreviation: MOVNS: multi-objective variable neighbourhood search; DES: discrete-event simulation; SO: simulation-optimization; AG: Alternative Graph; FCFS: First Come First Served; MIP: mixed integer programming; MILP: mixed-integer linear programming; B&B: branch and bound algorithm; VND: Variable Neighborhood Descent; NSGA-II: Non-dominated Sorting Genetic Algorithm–II; CD: crowding distance; DP: dynamic priority; EDD: earliest due date first; SRTT: shortest remaining traveling time; LST: least slack time first