A Processor for Genetic Algorithm using Dynamically Reconfigurable Memory

This paper proposes a novel processor for genetic algorithm (GA) using dynamically reconfigurable memory. In general GA, number of population is always constant. However, accuracy of solution is low at first-half stage. Therefore, the number of population is doubled at the expense of accuracy of solution, and the searching ability is improved at first-half stage in the proposed GA processor. Then, the number of population is reduced by half, and the accuracy is improved at second-half stage. As a result, the searching ability is improved without increasing memory capacity. The proposed GA processor was designed by using VHDL and simulated. The effectiveness of proposed architecture was confirmed with examples