Improved Genetic Algorithm with Gene Recombination for Bus Crew-Scheduling Problem

Author:

Song Cuiying1,Guan Wei2,Ma Jihui1,Liu Tao3

Affiliation:

1. MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, School of Traffic and Transportation, Beijing Jiaotong University, 3 Shang Yuan Cun, Haidian District, Beijing 100044, China

2. Institute of Systems Engineering and Control, School of Traffic and Transportation, Beijing Jiaotong University, 3 Shang Yuan Cun, Haidian District, Beijing 100044, China

3. Department of Civil and Environmental Engineering, Transportation Research Centre, The University of Auckland, 20 Symonds Street, Auckland 1142, New Zealand

Abstract

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.

Funder

National Basic Research Program of China

Publisher

Hindawi Limited

Subject

General Engineering,General Mathematics

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