Swarm-inspired optimization has become very popular in recent years. Particle swarm
optimization (PSO) and Ant colony optimization (ACO) algorithms have attracted the interest …

The purpose of this paper is to present a new hierarchic method based on swarm
intelligence algorithms for solving the well-known traveling salesman problem. The swarm …

In this paper, we show a survey of meta-heuristics algorithms based on grouping of animals
by social behavior for the Traveling Salesman Problem, and propose a new classification of …

The traveling purchaser problem (TPP) is a notable generalization of the traveling salesman
problem (TSP) which involves selecting a subset of markets at a minimum traveling cost …

Abstract The Mother Tree Optimization (MTO) algorithm is a new swarm intelligence
technique that we have recently proposed for solving continuous optimization problems …

Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) algorithms have
attracted the interest of researchers due to their simplicity, effectiveness and efficiency in …

Abstract The Hidden Markov Models (HMM) are a powerful statistical techniques for
modeling complex sequences of data. In this paper a Hidden Markov Model classifier is a …

It is known that some of the algorithms in optimization field have originated from inspiration
from animal behaviors in nature. Natural phenomena such as searching behavior of ants for …

In the ant colony system (ACS) algorithm, ants build tours mainly depending on the
pheromone information on edges. The parameter settings of pheromone updating in ACS …

Parameters values have significant effects on the performance of the ant colony system
(ACS) algorithm. However, it is a difficult task to choose proper parameters values for …