Journal
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
Volume 87, Issue -, Pages 130-148Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.tre.2016.01.004
Keywords
Subway station; Station service capacity; Uncertain demand; Genetic algorithm; Data envelopment analysis; Simulation optimization
Categories
Funding
- State Key Lab of Rail Traffic Control and Safety, China [RCS2015ZZ002, RCS2016ZT005, I15RC00070]
- National Natural Science Foundation of China [71501014, 71571012]
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This paper proposes a problem of passenger flow organization in subway stations under uncertain demand. The existing concepts of station service capacity are extended and further classified into three in different demand scenarios. Mathematical models are put forward to measure the three capacities and a unified simulation-based algorithm is developed to solve them. To increase computing speed, data envelopment analysis (DEA) and genetic algorithms (GA) are embedded in this algorithm. A case study will demonstrate the performance of the proposed algorithm and give a detailed procedure of passenger flow control based on station service capacity in various demand scenarios. (C) 2016 Elsevier Ltd. All rights reserved.
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