A variable-splitting Lagrangian decomposition for train timetabling and skip-stopping with train-type decision

Document Type

Journal Article

Publication Date

2024

Subject Area

mode - rail, operations - scheduling

Keywords

Train, timetabling, skip-stopping

Abstract

While designing the train timetabling and skip-stopping plan in a space–time network shared by multi-type trains, a prevailing approach is to predesignate a specific type for each train to simplify the problem. However, such a setting is unreasonable and inaccurate to a considerable extent. This paper focuses on how to jointly optimize the train timetabling and skip-stopping problem with train-type decision for a high-speed rail corridor. With the help of a time-dependent and preference-grouped demand representation, this problem is formulated as an integer linear programming model, in which the optimization objective is to minimize the total train- and passenger-related costs. Under the Lagrangian relaxation framework, we employ a variable-splitting technique to decompose the proposed model into several solvable subproblems. By further exploiting the dual solution information, a three-stage heuristic method is developed to generate the expected feasible solution to the problem under consideration. Finally, we conduct a series of numerical experiments to demonstrate the efficiency and effectiveness of the proposed approach.

Rights

Permission to publish the abstract has been given by Elsevier, copyright remains with them.

Comments

Transportation Research Part C Home Page:

http://www.sciencedirect.com/science/journal/0968090X

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