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粒子群优化的私人小客车短途合乘定价策略

Pricing Strategy of Short Distance Private Car Ride-sharing Based on Particle Swarm Optimization
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摘要 针对私人小客车短途合乘存在的定价不合理、难以长期发展等问题,本文提出一种改进的定价策略。首先,基于上海市短途通勤情景,考虑合乘参与者的费用成本、时间成本、迟到风险等出行成本,通过演化博弈模型对固定费用模式与固定上限模式进行了模拟,宏观分析现有定价策略的发展趋势。然后,提出了动态折算模式,引入折算比例参数,比较不同折算比例时的演化规律,确定合乘参与者均受益的折算比例范围。最后,通过粒子群优化求得折算比例的最优解,从而确定新的定价模型。本文提供的私人小客车短途合乘定价优化策略可以有效促进出行者选择合乘,有利于合乘行业可持续发展。 Aiming at the problems of unreasonable pricing and difficult long-term development of short distance private car ride-sharing, this paper proposes an improved pricing strategy. Firstly, based on the short-distance commuting scenario in Shanghai, considering the travel costs such as the expense cost, time cost and the risk of tardiness of the participants, the fixed cost model and fixed ceiling model are simulated through the evolutionary game model, and the development trend of the existing pricing strategy is analyzed macroscopically. Then, a dynamic conversion model is proposed, and the conversion proportion parameter is introduced to compare the evolution rules of different conversion proportions, so as to determine the conversion proportion range for the benefit of multiplication participants. Finally, the optimal solution of the conversion ratio is obtained through particle swarm optimization, so as to determine the new pricing model.The pricing optimization strategy of private minibus short distance ride in this paper can effectively promote travelers to choose ride in, which is conducive to the sustainable development of ride in industry.
作者 孔德洋 黄偲蕊 麻殊捷 KONG Deyang;HUANG Sirui;MA Shujie(School of Automotive Studies,Tongji University,Shanghai 201804,China)
出处 《综合运输》 2022年第8期110-115,共6页 China Transportation Review
基金 上海市科委科普项目(20DZ2306500)。
关键词 城市交通 定价策略 粒子群优化 私人小客车合乘 演化博弈模型 Urban traffic Pricing strategy PSO Private car ride-sharing Evolutionary game model
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