Crew Planning Optimization Model of High-Speed Railway

被引：1
|
作者：
Li, Jinmei [1 ]
Nie, Lie [1 ]
机构：
[1] Beijing Jiaotong Univ, Sch Traff & Transportat, Beijing 100044, Peoples R China
来源：
SUSTAINABLE DEVELOPMENT OF INDUSTRY AND ECONOMY, PTS 1 AND 2 | 2014年 / 869-870卷
关键词：
crew planning; Genetic Algorithm; Simulated Annealing Algorithm; crew scheduling; crew rostering; TSP;
D O I：
10.4028/www.scientific.net/AMR.869-870.298
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
Crew planning with complicated constraints is decomposed into two sequential phases: crew scheduling phase, crew rostering phase. Setting a dynamic model based on set covering model, Genetic Algorithm is adopted based on feasible solution range in search of optimal scheduling set with minimum time. Constructing a node-arc TSP network, it adopts Genetic Algorithm and Simulated Annealing Algorithm to create a work roster. Based on Wuhan-Guangzhou High-Speed Railway in China, the balance degree of crew planning is measured by crew working time entropy. The proposed model proves strong practical application.
引用
收藏
页码：298 / 304
页数：7
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