Evolutionary computing in operational research for two-layer neural networks

Considering the non-linear characteristics of the activation functions, the entire task is multidimensional and non-linear with a multimodal target function. Implementing evolutionary computing in the multimodal optimization tasks gives developers new and effective tools for seeking the global minimum. A developer has to find the optimal and simple transformation between the realization of a phenotype and a genotype. In the article, a two-layer neural network is analysed. In the first step, the population is created. In the main algorithm loop, a parent selection mechanism is used together with the fitness function. To evaluate the quality of evolutionary computing process different measured characteristics are used. The final results are depicted using charts and tables.