An Imanishian genetic algorithm for the optimum design of surface acoustic wave filter

Abstract

The frequency response characteristics of surface acoustic wave (SAW) filters are governed primarily by their geometrical structures, i.e., the configurations of interdigital transducers (IDTs) and reflectors arranged on piezoelectric substrates. We present an Imanishian genetic algorithm (GA), which is based on an evolutionary theory advocated by a Japanese ecologist, Kinji Imanishi, for the structural design of SAW filters. In the proposed Imanishian GA, each species is discriminated from others according to the distance between individuals. Then, the generation model tries to hold various species in the population as many as possible. In addition, a local search is used to improve respective individuals effectively. As a result, in comparison with traditional Darwinian GAs, the Imanishian GA is better at taking balance between exploration and exploitation. Computational experiments conducted on an optimum design of a resonator type SAW filter demonstrate the usefulness of the Imanishian GA.