微分进化算法在高铁票价双层规划模型求解中的应用
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摘要
微分进化算法(DE)是一种快速高效的智能进化算法,本文对其算法做了简单的介绍,并针对高速铁路票价问题,引入并构建了双层规划模型。模型中高铁企业是领导者角色,出行乘客是跟随者角色,二者相互作用。上层模型从高铁企业收益最大化的角度出发,下层模型以各类出行方式的乘客广义出行费用相同为基础。针对该模型设定了一些参数,并介绍了如何应用微分进化算法对该模型进行求解,并对乘客福利及算法本身的优化工作做出了进一步设想。
Differential evolution(DE) is a fast and efficient intelligent evolutionary algorithm,and its algorithm is briefly introduced.Aiming at the problem of high-speed railway fare,a bi-level programming model is introduced and constructed.In the model,the high-speed railway enterprise is the leader role,and the traveling passenger is the follower role,which interact with each other.The upper model is based on maximizing the revenue of high-speed railway enterprises,and the lower model is based on the same generalized travel cost of passengers in different modes of travel.Some parameters are set for the model,and how to use differential evolution algorithm to solve the model is introduced.Further assumptions are made on passenger welfare and optimization of the algorithm itself.
Differential evolution(DE) is a fast and efficient intelligent evolutionary algorithm,and its algorithm is briefly introduced.Aiming at the problem of high-speed railway fare,a bi-level programming model is introduced and constructed.In the model,the high-speed railway enterprise is the leader role,and the traveling passenger is the follower role,which interact with each other.The upper model is based on maximizing the revenue of high-speed railway enterprises,and the lower model is based on the same generalized travel cost of passengers in different modes of travel.Some parameters are set for the model,and how to use differential evolution algorithm to solve the model is introduced.Further assumptions are made on passenger welfare and optimization of the algorithm itself.
引文
[1]崔伟.高速铁路客运定价理论与方法研究[D].兰州:兰州交通大学,2013.
[2]刘科.改进微分进化算法在LZ-AVC6000系统中的研究与应用[D].保定:华北电力大学,2017.
[3]韦凌翔,陈红,蒋金亮,等.基于广义费用函数的高铁票价双层规划模型研究[J].铁道科学与工程学报,2015,12(2):250-256.
[4]徐冰.基于铁路客运票价的定价模型及求解方法研究[D].沈阳:沈阳工业大学,2007.
[5]陈建华,高自友.基于双层规划模型的铁路票价制定优化策略[J].北方交通大学学报(社会科学版),2003(3):38-41.
[6]程谦.双层规划模型在沪宁城际铁路客票价格优化中的应用[J].现代交通技术,2015,12(2):77-80.
[7]四兵锋,高自友.市场竞争条件下的客运价格优化策略模型及算法[J].交通运输系统工程与信息,2007(1):73-79.
[8]高自友,四兵锋.市场竞争条件下铁路旅客票价制定的模型与算法[J].交通运输系统工程与信息,2001(1):50-55.
[9]陈建华.铁路旅客票价优化问题的相关模型及算法[D].北京:北京交通大学,2007.
[10]郝鹏海,程晓荣.粒子群算法在铁路双层规划模型求解中的应用[J].电脑知识与技术,2017,13(26):238-239+242.
[2]刘科.改进微分进化算法在LZ-AVC6000系统中的研究与应用[D].保定:华北电力大学,2017.
[3]韦凌翔,陈红,蒋金亮,等.基于广义费用函数的高铁票价双层规划模型研究[J].铁道科学与工程学报,2015,12(2):250-256.
[4]徐冰.基于铁路客运票价的定价模型及求解方法研究[D].沈阳:沈阳工业大学,2007.
[5]陈建华,高自友.基于双层规划模型的铁路票价制定优化策略[J].北方交通大学学报(社会科学版),2003(3):38-41.
[6]程谦.双层规划模型在沪宁城际铁路客票价格优化中的应用[J].现代交通技术,2015,12(2):77-80.
[7]四兵锋,高自友.市场竞争条件下的客运价格优化策略模型及算法[J].交通运输系统工程与信息,2007(1):73-79.
[8]高自友,四兵锋.市场竞争条件下铁路旅客票价制定的模型与算法[J].交通运输系统工程与信息,2001(1):50-55.
[9]陈建华.铁路旅客票价优化问题的相关模型及算法[D].北京:北京交通大学,2007.
[10]郝鹏海,程晓荣.粒子群算法在铁路双层规划模型求解中的应用[J].电脑知识与技术,2017,13(26):238-239+242.