Improved Genetic Algorithm with Gene Recombination for Bus Crew-Scheduling Problem
Joint Authors
Song, Cuiying
Liu, Tao
Guan, Wei
Ma, Jihui
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-09-07
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
This paper presents an improved genetic algorithm (GA) with gene recombination for bus crew-scheduling problem in bus company.
Unlike existing methods that rely on designing a fixed potential shift set by software, our new method does not need such a potential shift set information.
In our method, satisfied shifts are generated through gene recombination in genetic algorithm.
We conduct extensive studies based on real-life instances from Beijing Bus Group.
Compared with results generated by the current manual method, ant colony algorithm, and CPLEX, computational results show that our algorithms demonstrated very good computational performances.
In our tests, the number of the maximum reducing shifts can be beyond 30, especially when trip number is very large.
The high relative percentage deviation demonstrated the effectiveness of the algorithm proposed.
American Psychological Association (APA)
Song, Cuiying& Guan, Wei& Ma, Jihui& Liu, Tao. 2015. Improved Genetic Algorithm with Gene Recombination for Bus Crew-Scheduling Problem. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-14.
https://search.emarefa.net/detail/BIM-1074567
Modern Language Association (MLA)
Song, Cuiying…[et al.]. Improved Genetic Algorithm with Gene Recombination for Bus Crew-Scheduling Problem. Mathematical Problems in Engineering No. 2015 (2015), pp.1-14.
https://search.emarefa.net/detail/BIM-1074567
American Medical Association (AMA)
Song, Cuiying& Guan, Wei& Ma, Jihui& Liu, Tao. Improved Genetic Algorithm with Gene Recombination for Bus Crew-Scheduling Problem. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-14.
https://search.emarefa.net/detail/BIM-1074567
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1074567