基于群体进化的高铁民航客运票价优化模型

Fare Optimization Model of High-speed Rail and Civil Aviation Based on Group Evolution under Elastic Demand

为研究市场竞争条件下高铁与民航的票价优化问题,建立了二者相互博弈的双层规划模型,上层规划以票价决为决策变量,以实现运输经济效益最大化为决策目标;下层规划以旅客群体为决策主体,以广义出行费用最小化为决策目标。在旅客群体有限理性的刻画方面,采用三维元胞遗传算法的思想对旅客群体针对广义出行费用的进化寻优过程进行动态描述,以动态规则运算取代传统基于随机用户均衡思想的logit分流模式。最后利用基于灵敏度分析的启发式算法求解双层规划。研究发现:新模型较好的体现了旅客群体均衡配流的形成过程及旅客群体的有限理性特点对票价均衡形成过程的影响。

In order to study the fare optimization of high speed railway and civil aviation under competition condition,a bilevel programming with mutual gambling is established,in which the upper-level programming contains the decision variable of ticker price with the decision goal of maximizing the economic benefit and the lower-level of programming contains decision-makers of passengers with the decision goal of minimizing the generalized travel cost.In depicting passengers' bounded rationality,the idea of 3-D cellular genetic algorithm is introduced to describe passengers' evolving optimization procedure on generalized travel cost;the logit model of traditional stochastic user equilibrium assignment model is replaced by dynamic regular expression.The bi-level programming is solved by heuristic algorithm based on sensitivity analysis.The research shows that the new model reflecs the formation process of passengers' equilibrium assignment and the impacts of passengers bounded rationality on the formation process of equilibrium.