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A Bi-level Programming Model and Solution Algorithms for Taxi Fare in Taxi Market of China

机译:中国出租车市场出租车票价的双层规划模型和求解算法

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摘要

The hearing system provides a game platform for dealing with the optimization problem of taxi fare due to the taxi market regulations and the variation of operating cost in taxi market of China. In this paper, a bi-level programming model is proposed for optimization of taxi fare in monopoly market, as simultaneously considers the equilibrium between the social welfare and profit of taxi firms. The upper-level problem is a set of formulations ensuring maximization of social welfare under constrain on taxi fare restriction of government in taxi industry. The lower-level model aims to maximize the profit of taxi firms from fare revenue and maintains the positive value of firm profit and supply-demand equilibrium of taxi market. The Lagrangian approach is used to transform the lower model into upper model with K-K-T conditions, and the bi-level programming model becomes a single-level programming model. The Genetic Algorithm and Simulated Annealing algorithm are respectively designed to solve the model. A numerical calculation is presented to illustrate the accuracy and efficiency of proposed model and algorithms in a real urban road network of Harbin.
机译:该听觉系统提供了一个游戏平台,用于解决由于出租车市场法规和中国出租车市场运营成本变化而导致的出租车票价优化问题。本文提出了一种双层规划模型来优化垄断市场的出租车票价,同时考虑了出租车公司的社会福利与利润之间的平衡。较高层次的问题是在出租车行业政府的出租车费用限制的约束下,确保社会福利最大化的一系列公式。下层模型旨在使出租车公司从票价收入中获得最大利润,并保持公司利润的正值和出租车市场的供需平衡。拉格朗日方法用于将下层模型转换为具有K-K-T条件的上层模型,并且双层编程模型成为单层编程模型。设计了遗传算法和模拟退火算法对模型进行求解。进行了数值计算,以说明所提出的模型和算法在哈尔滨真实城市道路网中的准确性和效率。

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