Title

Demand-driven timetable and stop pattern cooperative optimization on an urban rail transit line

Document Type

Journal Article

Publication Date

2020

Subject Area

place - asia, place - urban, mode - rail, mode - subway/metro, operations - coordination, operations - scheduling, planning - service improvement, ridership - demand

Keywords

Train timetable, train stop pattern, time-dependent passenger demand, mixed-integer linear programming, genetic algorithm, case study

Abstract

This study proposes a modelling framework for the demand-driven train timetable and stop pattern cooperative optimization problem on an urban rail transit line. By embedding the train stop pattern into the timetable optimization process, we consider the minimization of total passenger travel time. A binary variable determination (BVD) method, which can transform complicated linear constraints into simple logical constraints, is proposed to calculate the large number of binary variables easily, and a genetic algorithm (GA) based on the BVD method is designed to solve the proposed model. A case study of the Batong line in the Beijing subway network is conducted to test the proposed model and algorithm. This study can provide beneficial advice for the operator to improve the operational service of urban rail transit lines.

Rights

Permission to publish the abstract has been given by Taylor&Francis, copyright remains with them.

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