在考虑随机需求的情况下,对高速铁路的超额预订和座位分配进行联合优化
Jing Xu1, Lianbo Deng1, Xinlei Hu1
1School of Traffic and Transportation Engineering, Central South University, Changsha, Hunan, China.
PloS one
|November 18, 2024
概括
这项研究优化了高速铁路 (HSR) 超额预订和座位分配,通过解决随机的乘客不出现来最大限度地提高收入. 拟议的联合优化方法有效地减少了空座位,并增加了预期收入.
科学领域:
- 运营研究 运营研究
- 运输科学 运输科学
- 应用数学 应用数学 应用数学
背景情况:
- 高速铁路 (HSR) 的乘客不出现导致大量的空座损失和收入减少.
- 现有的座位分配策略往往无法解释乘客需求和不出现行为的随机性质.
- 有效的收入管理对于HSR运营的利能力和效率至关重要.
研究的目的:
- 开发一个共同的优化模型,在HSR中对超额预订和座位分配进行优化,以减轻空座损失.
- 通过考虑乘客需求分布和各种运营约束来最大限度地提高HSR的预期收入.
- 设计一个有效的算法来解决复杂的随机优化问题.
主要方法:
- 制定了一个非线性随机编程模型,以共同优化超额预订和座位分配.
- 设计了一个多级优化算法,结合了采样平均近似方法.
- 优化问题被分解为代解决的子问题,解决需求和不显示的不确定性.
主要成果:
- 拟议的联合优化模型和算法有效地处理乘客需求和不出现行为的随机性.
- 数字研究证实,该方法显著提高了HSR的预期收入.
- 这种方法成功地弥补了由于乘客不出现而导致的空座损失.
结论:
- 对超额预订和座位分配的联合优化是提高HSR收入管理的可行策略.
- 开发的随机编程模型和算法为管理HSR操作中的不确定性提供了强大的解决方案.
- 实施这一战略可以导致更高效的资源利用和提高高速铁路系统的利能力.
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