Combination optimization for seat allocation of railway passenger car based on improved genetic algorithm

被引：0
|
作者：
Liu H. [1 ]
Cheng W. [1 ]
Zhang M. [1 ]
机构：
[1] School of Mechanical Engineering, Southwest Jiaotong University, Chengdu, 610031, Sichuan
来源：
Cheng, Wenming (wmcheng@swjtu.edu.cn) | 1600年 / Chinese Academy of Railway Sciences卷 / 37期
关键词：
Genetic algorithm; Railway passenger ticket; Seat allocation; Seat allotment; Ticket combination optimization; Utilization rate of passenger seat;
D O I：
10.3969/j.issn.1001-4632.2016.06.15
中图分类号：
学科分类号：
摘要：
In order to allocate train tickets for each station properly and raise the income of railway passenger transport, a mathematical model about the relations between train seats and tickets was established based on the actual situation of passenger train stopping at multiple stations. The genetic algorithm was improved in line with mathematical model and the characteristics of railway passenger flow, and ticket encoding methods corresponding to seat states were defined. Distinguished symbols were added into ticket codes to differentiate the combined conditions of ticket demand for riding interval. Since train seat allocation had the features of multiple-knapsack problem and its essence was the combinatorial optimization problem of train seat allocation, accordingly, combinatorial cross rules for ticket demand of riding interval were defined. Under the premise that the ticket demand of original riding interval always remained unchanged in the process of optimization operation, with the maximum passenger seat utilization rate and ticket revenue as the optimization objectives, the best offspring was chosen by improved genetic algorithm to iterate and conversely solve the seat allotment amount for each station. Meanwhile, the seat allocation and ticket combination optimization for passenger car were completed. The effectiveness of the proposed model and algorithm was verified by examples. © 2016, Editorial Department of China Railway Science. All right reserved.
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页码：113 / 120
页数：7
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