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Title: A comparison of heuristic algorithms for bus dispatch
Authors: Wang, H 
Zuo, L
Liu, J
Yang, C
Li, Y
Baek, J
Keywords: Bus dispatch
Dispatch time interval
Heuristic algorithm
Multiple objective optimization
Issue Date: 2017
Publisher: Springer
Source: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics), 2017, v. 10386, p. 511-518 How to cite?
Journal: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics) 
Abstract: Bus dispatch (BD) system plays an essential role to ensure the efficiency of public transportation, which has been frequently addressed by the heuristic algorithms. In this paper, five well-exploited heuristic algorithms, i.e. Genetic algorithm (GA), Particle Swarm Optimization (PSO), Artificial Bee Colony algorithm (ABC), Bacterial Foraging Optimization (BFO) and Differential Evolution algorithm (DE), are employed and compared for solving the problem of BD. The comparison results indicate that DE is the best method in dealing with the problem of BD in terms of mean, minimum, and maximum, while BFO obtains the minor lower value of standard deviation and achieves the similar convergence speed in comparison to DE. The performance of PSO seems to outperform the remaining two algorithms (i.e. ABC and GA) in most cases. However, among five algorithms, GA achieves the worst results in terms of the weight estimated objective (i.e. number of departures and average waiting time).
Description: 8th International Conference on Swarm Intelligence, ICSI 2017, 27 July 2017 - 1 August 2017
ISBN: 9783319618326
ISSN: 0302-9743
EISSN: 1611-3349
DOI: 10.1007/978-3-319-61833-3_54
Appears in Collections:Conference Paper

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