A Self-adaptive Evolutionary Programming Based on Optimum Search Direction

The Classical Evolutionary Programming (CEP) relies on Gaussian mutation, whereas Fast Evolutionary Programming (FEP) selects Cauchy distribution as the primary mutation operator, Improved Fast Evolutionary (IFEP) selects the better Gaussian and Cauchy distribution as the primary mutation operator. In this paper, we propose a self-adaptive Evolutionary Programming based on Optimum Search Direction (OSDEP) in which we introduce the current best global individual into mutation to guide individuals to converge according to the global search direction. Extensive empirical studies have been carried out to evaluate the performance of OSDEP, IFEP, FEP and CEP. From the experimental results on seven widely used test functions, we can show that OSDEP outperforms all of IFEP, FEP and CEP for all the test functions.

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