Generation Methods of Neighborhood Schedules for Practical Train Crew Scheduling Problems Using Tabu Search

被引：0
|
作者：
Kokubo, Tatsuya [1 ]
Fukuyama, Yoshikazu [1 ]
机构：
[1] Meiji Univ, Grad Sch Adv Math Sci, Nakano Ku, Tokyo, Japan
来源：
2017 IEEE 10TH INTERNATIONAL WORKSHOP ON COMPUTATIONAL INTELLIGENCE AND APPLICATIONS (IWCIA) | 2017年
关键词：
train crew scheduling problem; tabu search; combinational optimization problem;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper proposes generation methods of neighborhood schedules for crew scheduling problems (CSPs) in order to apply to practical problems. The proposed methods can give diversification to neighborhood schedules and generate an appropriate schedule. The results indicate that the proposed methods can drastically reduce the objective function values for the actual timetable than the conventional method.
引用
收藏
页码：39 / 44
页数：6
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