Highlights This paper formally introduces and models the destination-reachability based last train timetabling problem (DR-LTTP in abbreviation) in URT networks, which involves both the last train timetabling and the passenger path choice/assignment. The DR-LTTP is skilfully formulated as a mix integer linear programming (MILP) model, which is solvable for large-size problems with standard solvers such as CPLEX and GAMS. We put forward three methods to simplified the URT network and reduce the computational burden without jeopardizing the solution quality. We test our model in a real large-size Beijing URT network and the results show the applicability and efficiency of the proposed model. More passengers can reach their destination stations with our optimized last train timetable compared to the published one.
Abstract As urban rail transit (URT) systems usually do not operate for the whole day, the last train service offers the last daily chance for late-night passengers to utilize URT services to reach their target destination stations. This paper formally introduces and models the destination-reachability based last train timetabling problem (DR-LTTP in abbreviation) in URT networks, which involves both the last train timetabling and the passenger assignment. The DR-LTTP is formulated as a mixed integer linear programming and can be solved by existing commercial optimization software. The model is illustrated with a simple numerical example on a minimum spanning tree network, and comparison experiments are conducted between DR-LTTP model and station-transferability based last train timetabling problem (ST-LTTP in abbreviation). Finally, a real case study with Beijing URT network is conducted to test the performance of our model.
Last train scheduling for maximizing passenger destination reachability in urban rail transit networks
Transportation Research Part B: Methodological ; 129 ; 79-95
2019-09-03
17 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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