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Capacity-oriented passenger flow control under uncertain demand: Algorithm development and real-world case study |
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| Institution: | 1. State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China;2. Traffic Operations and Safety (TOPS) Laboratory, Department of Civil and Environmental Engineering, University of Wisconsin-Madison, WI 53706, USA;1. State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, 100044, Beijing, China;2. Rotterdam School of Management, Erasmus University Rotterdam, 3000 DR, Rotterdam, The Netherlands;3. Department Process quality and Innovation, Netherlands Railways, 3500 HA, Utrecht, The Netherlands |
| Abstract: | 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. |
| Keywords: | Subway station Station service capacity Uncertain demand Genetic algorithm Data envelopment analysis Simulation optimization |
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