Abstract Ant Colony Optimization (ACO) is a metaheuristic that is inspired by the pheromone
trail laying and following behavior of some ant species. Artificial ants in ACO are stochastic …

This article presents an overview of recent work on ant algorithms, that is, algorithms for
discrete optimization that took inspiration from the observation of ant colonies' foraging …

Social insects--ants, bees, termites, and wasps--can be viewed as powerful problem-solving
systems with sophisticated collective intelligence. Composed of simple interacting agents …

Swarm intelligence is a relatively new approach to problem solving that takes inspiration
from the social behaviors of insects and of other animals. In particular, ants have inspired a …

Advances in processor, memory and radio technology will enable small and cheap nodes
capable of sensing, communication and computation. Networks of such nodes can …

Advances in processor, memory, and radio technology enable small and cheap nodes
capable of sensing, communication, and computation. Networks of such nodes can …

Conclusions The field of ACO algorithms is very lively, as testified, for example, by the
successful biannual workshop (ANTS—From Ant Colonies to Artificial Ants: A Series of …

Hybrid metaheuristics have received considerable interest these recent years in the field of
combinatorial optimization. A wide variety of hybrid approaches have been proposed in the …

Ant colonies, and more generally social insect societies, are distributed systems that, in spite
of the simplicity of their individuals, present a highly structured social organization. As a …

Advances in microsensor and radio technology enable small but smart sensors to be
deployed for a wide range of environmental monitoring applications. The low-per node cost …