DocumentCode
2787532
Title
Parallel implementation of ant colony optimization on MPP
Author
Chen, Ling ; Sun, Hai-ying ; Wang, Shu
Volume
2
fYear
2008
fDate
12-15 July 2008
Firstpage
981
Lastpage
986
Abstract
An adaptive parallel ant colony algorithm (PACO) is presented. In the algorithm, we propose a strategy for information exchange between processors which make each processor choose its partner to communicate and update the pheromone adaptively. We also propose a method of adjusting the time interval of information exchange adaptively according to the diversity of the solutions so as to increase the ability of search and avoid early convergence. Experimental results show that our algorithm PACO has high convergence speed, high speedup and efficiency.
Keywords
convergence; parallel algorithms; search problems; adaptive parallel ant colony optimization algorithm; adaptive pheromone update; convergence speed; information exchange time interval; massive parallel processors; processor communication; processor information exchange; search ability; traveling salesman problem; Ant colony optimization; Computer science; Convergence; Cybernetics; Fault detection; Frequency; Load management; Machine learning; Software algorithms; Traveling salesman problems; Ant colony optimization; Diversity; Parallel; Traveling Salesman Problem;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2008 International Conference on
Conference_Location
Kunming
Print_ISBN
978-1-4244-2095-7
Electronic_ISBN
978-1-4244-2096-4
Type
conf
DOI
10.1109/ICMLC.2008.4620547
Filename
4620547
Link To Document