Abstract
In many metaheuristics, such as simulated annealing or genetic algorithm, the aim of optimization is to obtain better results at the end of the search process. However, It is more useful to be able to get better results, also in the early stage of the search process. In this paper, we propose a new “agent search” method with the goal of obtaining better results not only at the end of the search process, but also in the early stage of the search process. In our method, a number of “search agents” autonomously explore for better solutions in the solution space, by means of several neighborhoods with different sizes. Some “manager agents” modify the status of each search agent under control, by two operations (“transfer” and “transport”) for the improvement of effectiveness of the exploration. The speed of searching of each search agent is measured, in order to decide the timing and kind of the operation. Our method has applied to passive filter synthesis for performance evaluation, and acceptable filter has been synthesized automatically.
