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An integrated pricing/planning strategy to optimize passenger rail service with uncertain demand

机译:优化乘客铁路服务,不确定需求的综合定价/规划战略

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摘要

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.
机译:以市场为导向的铁路运营规划和定价是增强铁路部门竞争力和吸引力的两个关键问题。在该研究领域的最新技术的限制是,供应方(操作规划)和需求侧问题(受定价影响)通常是单独考虑的。本文的贡献是提出一种基于动态票价,乘客需求的弹性,灵活调度,将这两个维度集成的收入最大化模型。该模型考虑了由铁路服务运营商直接承担的运营成本,并且由于乘客而被乘客因不良旅行时间的宿舍(即时间的价值)间接被乘客产生的成本。确定利润最大化的联合定价/调度战略的策略是基于Lyapunov优化。 Lyapunov优化应用于获得完全分布的低复杂性多插槽算法,只需要了解瞬时系统状态。我们在优化目标和队列积压之间证明了显式权衡。广州 - 深圳铁路(广东,中国)被雇用为实证案例研究,揭示了拟议模型的性质。

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