Cultural Evolution Algorithm for Global Optimizations and its Applications

The course of socio-cultural transition can neither be aimless nor arbitrary, instead it requires a clear direction. A common goal of social species' evolution is to move towards an advanced spiritual and conscious state. This study aims to develop a population-based algorithm on the basis of cultural transition goal. In this paper, the socio-cultural model based on a system thought framework could be used to develop a cultural evolution algorithm (CEA). CEA leverage four strategies, each consists of several search methods with similar thinking. Seven benchmark functions are utilized to validate the search performance of the proposed algorithm. The results show that all of the four strategies of cultural evolution algorithm have better performance when compared with relevant literatures. Finally, the CEA was then applied to optimize two different reliability engineering problems, a Serial-Parallel System design and a Bridge System design. For the Serial-Parallel System design, the CEA achieved the exact solution with ease, and for the Bridge System design, the solution obtained by the CEA is superior to those from other literatures.