DocumentCode :
1802898
Title :
The application of the improved Ant Colony Algorithm in mine locomotive scheduling problem
Author :
Guo-ning Gan ; Ting-lei Huang ; Shuai Gao
Author_Institution :
School of Computer science and engineering, Guilin University of Electronic Technology, China
fYear :
2013
fDate :
1-8 Jan. 2013
Firstpage :
1
Lastpage :
4
Abstract :
Ant Colony Algorithm has some advantages in solving complex optimization problems, in particular discrete optimization problem. A mine locomotive scheduling algorithm based on the improved Ant Colony Algorithm for the mine locomotive scheduling problem has proposed in this paper. The method takes simulated annealing algorithm as a local search strategy of ant colony algorithm, aim at expanding the solution search space, avoiding falling into local optimum that improve convergence rate of the algorithm by dynamic pheromone evaporation factor. Simulation results show that the algorithm is more efficiency in locomotive scheduling than the basic ant colony algorithm.
Keywords :
Annealing; Educational institutions; Shafts; Ant Colony Algorithm; Simulated Annealing Algorithm; pheromone; transportation scheduling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Conference Anthology, IEEE
Conference_Location :
China
Type :
conf
DOI :
10.1109/ANTHOLOGY.2013.6784852
Filename :
6784852
Link To Document :
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