Empirical study on the effect of population size on MAX-MIN ant system in dynamic environments
In this paper, the effect of the population size on the performance of the MAX -MIN ant system for dynamic optimization problems (DOPs) is investigated. DOPs are generated with the dynamic benchmark generator for permutation-encoded problems. In particular, the empirical study investigates: a) possible dependencies of the population size parameter with the dynamic properties of DOPs; b) the effect of the population size with the problem size of the DOP; and c) whether a larger population size with less algorithmic iterations performs better than a smaller population size with more algorithmic iterations given the same computational budget for each environmental change. Our study shows that the population size is sensitive to the magnitude of change of the DOP and less sensitive to the frequency of change and the problem size. It also shows that a longer duration in terms of algorithmic iterations results in a better performance.
The file attached to this record is the author's final peer reviewed version.
Citation : Mavrovouniotis, M. and Yang, S. (2015) Empirical study on the effect of population size on MAX-MIN ant system in dynamic environments. Proceedings of the 2016 IEEE Congress on Evolutionary Computation, to appear, 2016
Research Group : Centre for Computational Intelligence
Research Institute : Institute of Artificial Intelligence (IAI)
Peer Reviewed : Yes