|Title:||Dynamic Neighborhood Structures in Parallel Evolution Strategies|
|Abstract:||Parallelizing 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.|
|Appears in Collections:||Sonderforschungsbereich (SFB) 531|
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