In this paper, we present an improved continuous ant colony algorithm for global optimization of continuous functions. We show how to improve the quality of Ant Colony Optimization, ACO, to solve continuous optimization problems. We present the general idea, implementation, the analysis of its convergence and results obtained. We compare the results with Adaptive Genetic Algorithm, AGA, and Con...

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...

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...

A method of automatic programming, called genetic programming, assumes that the desired program is found by using a genetic algorithm. We propose an idea of ant colony programming in which instead of a genetic algorithm an ant colony algorithm is applied to search for the program. The test results demonstrate that the proposed idea can be used with success to solve the approximation problems.