Mehnen, JörnRudolph, GünterWeinert, Klaus2004-12-072004-12-0720012001-10-30http://hdl.handle.net/2003/541110.17877/DE290R-15247Parallelizing is a straightforward approach to reduce the total computation time of evolutionary algorithms. Finding an appropriate communication network within spatially structured populations for improving convergence speed and convergence probability is a difficult task. A new method that uses a dynamic communication scheme in an evolution strategy will be compared with conventional static and dynamic approaches. The communication structure is based on a socalled diffusion model approach. The links between adjacent individuals are dynamically chosen according to deterministic or probabilistic rules. Due to self-organization effects, efficient and stable communication structures are established that perform robust and fast on a multimodal test function.enUniversität DortmundReihe Computational Intelligence ; 112004report