Organizational evolutionary applied on geometric constraints solving
Duo Wang, Wenhui Li, Yi Rongqing, Xiaochun Cheng · 2008
In this paper, a new optimization method, Organizational Evolutionary Algorithm (OEA), is proposed, in which a population is made of organizations and whose evolution is led by three organizational evolutionary operators, i.e. the splitting operator, the merging operator and the cooperating operator; the splitting operator controls the size of organizations and make part of organizations enter into next generation directly, which are benefit for keeping the diversity of populations; the merging operator acts as a local searching function with taking advantage of leaders information; the cooperating operator increases the adaptability degree through the interactions of organizations. OEA is successfully applied to solve the non-linear parameterization design problems. Experiments show that OEA performs better than original Generic algorithm (GA) in this application of parameterization design.