Evolving Neural Networks Using Differential Evolution with Neighborhood-Based Mutation and Simple Subpopulation Scheme

This paper presents a method to search for near optimal neural networks. The proposed method combines Differential Evolution with Global and Local Neighborhood (DEGL) evolutionary algorithm and the multimodal technique Simple Subpopulation Scheme (SSS). The performance of the proposed method is investigated through experiments on six machine learning benchmarks for classification problems. The proposed method is competitive when compared to other methods of literature.