This paper presents a novel hybrid algorithm based on particle swarm optimization (PSO)
and ant colony optimization (ACO) and called hybrid ant particle optimization algorithm …

This paper presents the modified ant colony optimization (MACO) based algorithm to find
global optimum. Algorithm is based on that solution space of problem is restricted by the …

The ant colony optimization (ACO) algorithms are multi-agent systems in which the
behaviour of each ant is inspired by the foraging behaviour of real ants to solve optimization …

ABSTRACT A new versatile optimization approach referred to genetic ant colony algorithm
(GACA) combining both the genetic algorithm (GA) and the ant colony algorithm (ACA) is …

Hybrid algorithm is proposed to solve combinatorial optimization problem by using Ant
Colony and Genetic programming algorithms. Evolutionary process of Ant Colony …

We propose a novel hybrid algorithm named ACO–FA, which integrate ant colony
optimization (ACO) with firefly algorithm (FA) to solve unconstrained optimization problems …

In order to improve the global solving ability and convergence speed, avoid falling into local
optimal solution, the basic ant colony optimization (ACO) algorithm is improved to propose …

This article presents a heuristic particle swarm ant colony optimization algorithm to solve
engineering optimization problems. Although PSO has simple principle and ease to be …

In this paper, the ant colony optimization (ACO) method for solving optimal control problems
is investigated from parallel processing viewpoint. The OpenMP implementation of this …

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