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...

blind source separation technique separates mixed signals blindly without any information on the mixing system. in this paper, we have used two evolutionary algorithms, namely, genetic algorithm and particle swarm optimization for blind source separation. in these techniques a novel fitness function that is based on the mutual information and high order statistics is proposed. in order to evalu...

Optimization of reservoir parameters is an important issue in petroleum exploration and production. The Ant Colony Optimization(ACO) is a recent approach to solve discrete and continuous optimization problems. In this paper, the Ant Colony Optimization is usedas an intelligent tool to estimate reservoir rock properties. The methodology is illustrated by using a case study on shear wave velocity...

The ultimate goal of all optimization methods is to solve real-world problems. For a successful project execution, knowledge about optimization and the application has to be pooled. As it is too inefficient to highly train one person in both fields, a team of experts is usually put together. Unfortunately, communication errors must be expected when several people collaborate. In this work, we d...

MultiDisciplinary Optimization (MDO) problems represent one of the hardest and broadest domains of continuous optimization, often too complex to be tackled by classical optimization methods. We propose an original approach for taking into account this complexity using a self-adaptive multi-agent system where each elements of the problem become an agent in charge of a small part of the problem.

Approaches for the identification of piecewise affine systems are presented. The identification problem for piecewise affine systems is formulated as a smooth constrained, and a nonsmooth unconstrained optimization problem. The main advantage of the new problem formulations is the fact that no mixed integer problems have to be solved within this method. The feasibility and performance of the pr...

A novel version of Ant Colony Optimization (ACO) algorithms for solving continuous space problems is presented in this paper. The basic structure and concepts of the originally reported ACO are preserved and adaptation of the algorithm to the case of continuous space is implemented within the general framework. The stigmergic communication is simulated through considering certain direction vect...

This paper deals with discrete-event simulation based on optimization of a catchment basin management. The integration of optimization techniques into modeling and simulation relies on the evolution of the studied model using decisions based on previous simulation results. Three different categories of optimization via simulationmethods can be found in the literature: rank-and-selection methods...