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

Civil Engineering

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