Shrinking Neighborhood Evolution--a novel stochastic algorithm for numerical optimization

In this paper we develop and test a novel stochastic algorithm SNE (Shrinking Neighborhood Evolution) based on the issue of bound constrained optimization problem. Its heuristic strategy is simple and direct-related to the search region of the solving problem based on the concept of “k-box-neighborhood” -defined in this paper. Our numerical experiments show that the optimization capability of SNE is competing to other congeneric algorithms such as Particle Swarm Optimizer (PSO), Evolution Strategy with Covariance Matrix Adaptation (CMA-ES) and Differential Evolution (DE). The new method requires few control parameters, easy to use, and has promising potentials to parallel computation.