DocumentCode :
577610
Title :
An ant colony algorithm for permutation flow shop problem
Author :
Shang, Ke ; Feng, Zuren ; Ke, Liangjun
Author_Institution :
State Key Lab. for Manuf. Syst. Eng., Xi´´an Jiaotong Univ., Xi´´an, China
fYear :
2012
fDate :
6-8 July 2012
Firstpage :
596
Lastpage :
600
Abstract :
In this paper, a new ant colony optimization algorithm, called finite grade ant colony optimization, is proposed to solve permutation flow shop problem, its main characteristic is that the updated quantities of pheromone trails are independent of objective function values, and the heuristic information provide by Moccellin is adopted. The developed algorithm has been applied to the benchmark problems given by Taillard, Comparison results demonstrate that the performance of the proposed algorithm is promising.
Keywords :
ant colony optimisation; flow shop scheduling; Moccellin; ant colony optimization algorithm; finite grade ant colony optimization; heuristic information; objective function value; permutation flow shop problem; pheromone trail; Ant colony optimization; Benchmark testing; Cities and towns; Europe; Job shop scheduling; Linear programming; Traveling salesman problems; ant colony algorithm; finite grade pheromone; permutation flow shop problem;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation (WCICA), 2012 10th World Congress on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-1397-1
Type :
conf
DOI :
10.1109/WCICA.2012.6357949
Filename :
6357949
Link To Document :
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