%0 Journal Article
%T An Ant Colony Optimization Algorithm for Microwave Corrugated Filters Design
%A Ivan A. Mantilla-Gaviria
%A Alejandro D¨ªaz-Morcillo
%A Juan V. Balbastre-Tejedor
%J Journal of Computational Engineering
%D 2013
%R 10.1155/2013/942126
%X A practical and useful application of the Ant Colony Optimization (ACO) method for microwave corrugated filter design is shown. The classical, general purpose ACO method is adapted to deal with the microwave filter design problem. The design strategy used in this paper is an iterative procedure based on the use of an optimization method along with an electromagnetic simulator. The designs of high-pass and band-pass microwave rectangular waveguide filters working in the C-band and X-band, respectively, for communication applications, are shown. The average convergence performance of the ACO method is characterized by means of Monte Carlo simulations and compared with that obtained with the well-known Genetic Algorithm (GA). The overall performance, for the simulations presented herein, of the ACO is found to be better than that of the GA. 1. Introduction Several kinds of microwave filter design procedures have been proposed in the literature along the time. Almost all of them can be grouped into two categories; one of them includes those methods consisting of two stages; synthesis and optimization [1]. In the synthesis stage, techniques based on lumped elements and equivalences between these and physical models are used. The other category includes those approaches which are only based on the use of optimization techniques along with an electromagnetic simulator [1¨C4]. The procedure considered herein lays on the latter category. As described in [4], it is often necessary to implement two kinds of optimization: first, a global optimization method is used to find a roughly good solution and then local optimization is carried out to improve the previous solution. For the global optimization phase it is common to use some heuristic strategies [2¨C6] while for local optimization deterministic methods like the simplex method [7] or gradient based algorithms (e.g., the Broyden-Fletcher-Goldfarb-Shanno applied in [4]) are usually employed. The Ant Colony Optimization (ACO) is a kind of metaheuristic optimization method developed by Dorigo [8, 9]. The ACO is based on the communication system used by ants when they are looking for food sources. This system is an indirect system based on the modification of the physical environment by means of the segregation of a substance called pheromone [8, 9]. It has been widely applied to different engineering problems. However, in the electromagnetic community it has been mainly applied to the synthesis of antenna arrays [10¨C15], whilst only few applications have been found for the design of microwave filters. Particularly,
%U http://www.hindawi.com/journals/jcengi/2013/942126/