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 …

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 …

Ant Colony Optimization (ACO)[1, 2, 3] is a metaheuristic for solving hard combinatorial
optimization problems inspired by the indirect communication of real ants. In ACO …

Dealing with an excitation matching method, this paper presents a global optimization
strategy for the optimal clustering in sum-difference compromise linear arrays. Starting from …

Ant colony optimization is a metaheuristic that has been applied to a variety of combinatorial
optimization problems. In this paper, an ant colony optimization approach is proposed to …

Motivation: RNA sequence design is studied at least as long as the classical folding
problem. Although for the latter the functional fold of an RNA molecule is to be found, inverse …

In this paper, we consider combinatorial optimization problems with additional cardinality
constraints. In k-cardinality combinatorial optimization problems, a cardinality constraint …

This paper considers an efficient approximate algorithm for solving k-minimum spanning
tree problems which is one of the combinatorial optimization in networks. A new hybrid …

An analytical framework for investigating the finite-time dynamics of ant colony optimization
(ACO) under a fitness-proportional pheromone update rule on arbitrary construction graphs …

We present a novel approach to fully automated delineation of tree structures in noisy 2D
images and 3D image stacks. Unlike earlier methods that rely mostly on local evidence, our …