The Influence of Pheromone and Adaptive Vision in the Standard Ant Clustering Algorithm
Vahid Sherafat (State University of Campinas, Brazil), Leandro Nunes de Castro (Catholic University of Santos, Brazil) and Eduardo Raul Hruschka (Catholic University of Santos, Brazil)
Copyright: © 2005
Algorithms inspired by the collective behavior of social organisms, from insect colonies to human societies, promoted the emergence of a new field of research called swarm intelligence. The applications of swarm intelligence range from routing in telecommunication networks to robotics. This chapter discusses some of the ideas behind swarm intelligence, focusing on a clustering algorithm motivated by the social behavior of some ant species. The standard ant-clustering algorithm is presented; a brief review from the literature concerning the applications and variations of the basic model is provided; two novel modifications of the original algorithm are proposed and discussed; and a sensitivity analysis of the standard and modified algorithm in relation to some user-defined parameters is performed. A variation of a simple benchmark problem in the field is used to perform the sensitivity analysis of the algorithm and to assess the proposed modifications of the standard algorithm.