Analog circuit optimization via a modified Imperialist Competitive Algorithm

This paper proposes a novel evolutionary approach based on a modified Imperialist Competitive Algorithm for analog circuit design optimization. The original Imperialist Competitive Algorithm shows a low search ability in high-dimensional search spaces which is the case in optimization of analog circuits. The proposed tool addresses this problem by introducing a society-based algorithm with novel "selection" and "movement" operators. The tool is also equipped with a "mutation" operator increasing the search ability. A multi-dimensional analog design problem along with a mathematical benchmark are used to demonstrate its capability. Moreover, a thorough comparison between the original Imperialist Competitive Algorithm, the proposed algorithm and genetic algorithm as a reference is carried out. It will be revealed that the proposed algorithm is capable of exploring the cost space more efficiently resulting in better trade-offs between design objectives to reach better cost values. Additionally, the proposed algorithm is faster than the other under-test algorithms which is a key feature in simulation based optimization procedures.