The hydrophobic-polar model has been widely studied in the field of protein structure prediction both for theoretical purposes and as a benchmark for new optimization strategies. In this work we introduce a new heuristics based on Ant Colony Optimization and Markov Chain Monte Carlo that we called Hybrid Monte Carlo Ant Colony Optimization. We describe this method and compare results obtained o...

Ant colony optimization is a technique for optimization that was introduced in the early 1990’s. The inspiring source of ant colony optimization is the foraging behavior of real ant colonies. This behavior is exploited in artificial ant colonies for the search of approximate solutions to discrete optimization problems, to continuous optimization problems, and to important problems in telecommun...

Segmentation is one of the essential tasks in image processing. Thresholding is one of the simplest techniques for performing image segmentation. Multilevel thresholding is a simple and effective technique. The primary objective of bi-level or multilevel thresholding for image segmentation is to determine a best thresholding value. To achieve multilevel thresholding various techniques has been ...

This paper presents a modification of the ant colony optimization algorithm (ACO) intended to introduce psychology factor of emotion into the algorithm. We define only two emotions ants could have, positive and negative, and correspond to two reaction to perception respectively. For avoiding premature convergence allows Emotional Ant Colony Optimization (EACO) to continue search for better even...

In this paper we describe the application of an Ant Colony Optimization (ACO) algorithm to optimize the parameters in the design of PI controller and to find the best optimal intelligent controller. The ACO algorithm is a bio-inspired optimization method that has proven its success through various combinatorial optimization problems. The parameters of the PI Controller are evaluated by an ant c...

Over the last decade, evolutionary and meta-heuristic algorithms have been extensively used as search and optimization tools in various problem domains, including science, commerce, and engineering. Their broad applicability, ease of use, and global perspective may be considered as the primary reason for their success. Ant colony foraging behavior may also be considered as a typical swarm-based...

-Wireless Sensor Networks (WSN’s) have become an important and challenging research area in last year. Wireless Sensor Networks consisting of nodes with limited power are deployed to gather useful information from the field. In WSNs it is critical to collect the information in an energy efficient manner. Ant Colony Optimization, a swarm intelligence based optimization technique, is widely used ...

This paper presents a comparative study of Ant Colony and Genetic Algorithms for VLSI circuit bi-partitioning. Ant colony optimization is an optimization method based on behaviour of social insects [27] whereas Genetic algorithm is an evolutionary optimization technique based on Darwinian Theory of natural evolution and its concept of survival of the fittest [19]. Both the methods are stochasti...

The aim of this paper is compare the effect of using different topologies or connections between separate colonies in island based parallel implementations of the Ant Colony Optimization applied to the Minimum Weight Vertex Cover Problem. We investigated the sequential Ant Colony Optimization algorithms applied to the Minimum Weight Vertex Cover Problem before. Parallelization of population bas...