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作 者:苗蕾 王煜 MIAO Lei;WANG Yu(School of Traffic and Transportation,Beijing Jiaotong University,Beijing 100044,China;Institute of Computing Technology,China Academy of Railway Sciences Corporation Limited,Beijing 100081,China)
机构地区:[1]北京交通大学交通运输学院,北京100044 [2]中国铁道科学研究院集团有限公司电子计算技术研究所,北京100081
出 处:《铁道学报》2022年第7期21-26,共6页Journal of the China Railway Society
摘 要:高速铁路定期票产品目前主要依靠人工经验定价,急需理论研究成果支撑。提出一种基于单列车多停站下的定期票定价优化模型。首先在给定定期票产品的时间期限和乘车次数基础上,通过预期系数模拟识别定期票旅客数量并拟合其需求概率分布,其次,通过激励系数模拟旅客在购买定期票后乘车行为的变化,从而得到各区间非定期票旅客的需求分布函数,最终基于收益最大化构建单列车多停站下的定期票定价优化模型并利用粒子群算法求解。结果表明:提出的定价方法出售定期票产品能够比正常售票增加收益1.9%。激发了铁路运输企业进一步扩大推广定期票产品的积极性,也为通勤旅客带来更适合的运输产品,实现铁路运输企业与旅客的双赢。The periodic tickets provided by CHINA RAILWAY are now primarily priced based on experience,for which the theoretical research is much in need.A pricing optimization model for periodic tickets in the case of a single train with multiple stops is proposed in this paper.First,based on the given term and number of trips of periodic tickets,the expectation coefficient is used to simulate and identify the number of passengers with such tickets and fit the demand probability distribution.Second,the incentive coefficient is used to simulate the changes in the travel behavior of passengers who have bought periodic tickets,thus working out the demand distribution function of passengers who have no periodic tickets in each section.Finally,the pricing optimization model for periodic tickets in the case of a single train with multiple stops is established based on revenue maximization,and particle swarm optimization is adopted to solve it.The result shows that,compared with the conventional method,using the method proposed in this paper to price the periodic tickets can achieve an additional revenue of 1.9%,which not only motivates railway operators to further promote such tickets but also provides an option that is more suitable for commuting passengers,thus creating a win-win situation for both railway operators and passengers.
分 类 号:U292.31[交通运输工程—交通运输规划与管理]
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