Title
An analysis of communication policies for homogeneous multi-colony ACO algorithms
Abstract
The increasing availability of parallel hardware encourages the design and adoption of parallel algorithms. In this article, we present a study in which we analyze the impact that different communication policies have on the solution quality reached by a parallel homogeneous multi-colony ACO algorithm for the traveling salesman problem. We empirically test different configurations of each algorithm on a distributed-memory parallel architecture, and analyze the results with a fixed-effects model of the analysis of variance. We consider several factors that influence the performance of a multi-colony ACO algorithm: the number of colonies, migration schedules, communication strategies on different interconnection topologies, and the use of local search. We show that the importance of the communication strategy employed decreases with increasing search effort and stronger local search, and that the relative effectiveness of one communication strategy versus another changes with the addition of local search.
Year
DOI
Venue
2010
10.1016/j.ins.2010.02.017
Inf. Sci.
Keywords
Field
DocType
parallel algorithm,stronger local search,search effort,parallel hardware,aco algorithm,parallel homogeneous,communication strategy,distributed-memory parallel architecture,different communication policy,local search,fixed effects model,ant colony optimization,analysis of variance,parallelization,traveling salesman problem,distributed memory
Ant colony optimization algorithms,Communication policies,Mathematical optimization,Parallel algorithm,Computer science,Homogeneous,Algorithm,Schedule,Travelling salesman problem,Local search (optimization),Multiprocessor interconnection,Distributed computing
Journal
Volume
Issue
ISSN
180
12
0020-0255
Citations 
PageRank 
References 
32
1.27
27
Authors
5
Name
Order
Citations
PageRank
C. Twomey1321.27
T. Stutzle237419.71
Marco Dorigo3140311211.61
M. Manfrin4321.27
Mauro Birattari547130.81