Name
Title | ||
|---|---|---|
An integrated pricing/planning strategy to optimize passenger rail service with uncertain demand. |
Abstract | ||
|---|---|---|
The market-oriented rail operation planning and pricing are two key issues to enhance the competitiveness and attractiveness of rail sector. A limitation of the state-of-the-art in this area of research is that supply-side (operation planning) and demand-side issues (affected by the pricing) are generally considered separately. The contribution of this paper is to propose a revenue-maximization model that integrates these two dimensions, based on dynamic ticket-pricing, elasticity in passenger demand, and flexible dispatching. The model considers both operating costs directly borne by the rail service operator and costs indirectly incurred by passengers due to the disutility of unproductive travel time (i.e. the value of time). The strategy to identify the profit-maximizing joint pricing/dispatching strategy is based on Lyapunov optimization. The Lyapunov optimization is applied to obtain a fully distributed and low-complexity multi-slot algorithm only requiring knowledge of the instantaneous system state. We prove the explicit trade-off between the optimization objective and queue backlog. The Guangzhou-Shenzhen railway (Guangdong, China) is employed as the empirical case study, to expose the properties of the proposed model. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.3233/JIFS-181701 | JOURNAL OF INTELLIGENT & FUZZY SYSTEMS |
Keywords | Field | DocType |
Rail service planning,dynamic pricing,Lyapunov drift-plus-penalty,queue backlog,revenue management | Operations research,Artificial intelligence,Machine learning,Mathematics | Journal |
Volume | Issue | ISSN |
36 | 1 | 1064-1246 |
Citations | PageRank | References |
2 | 0.35 | 12 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaoqiang Zhang | 1 | 145 | 31.20 |
| Lin Li | 2 | 323 | 79.92 |
| Scott Le Vine | 3 | 4 | 0.71 |
| Xiaobo Liu | 4 | 12 | 2.30 |