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Particle Swarm Optimization (PSO) is an optimization method that is inspired by nature and is used frequently nowadays. In this paper we proposed a new dynamic geometric neighborhood based on Voronoi diagram in PSO. Voronoi diagram is a geometric naturalistic method to determine neighbors in a set of particles. It seems that in realistic swarm, particles take Voronoi neighbors into account. Also a comparison is made between the performance of some traditional methods for choosing neighbors and new dynamic geometric methods like Voronoi and dynamic Euclidean. In this comparison it is found that PSO with geometric neighborhood can achieve better accuracy overall especially when the optimum value is out of the initial range.