Сибирский федеральный университет

Тип публикации: статья из журнала

Год издания: 2017

Ключевые слова: genetic algorithms, genetic programming, constructive hyper-heuristic, selection operator

Аннотация: Genetic algorithms must be fine-tuned in order to achieve the best results. In this study, we have proposed a new hyper-heuristic based on genetic programming for the automated synthesis of a selection operator in genetic algorithms. Black-Box Optimization Benchmarking is used as a training set and as a test set for estimating the generalization ability of a synthesized selection operator. The results of numerical experiments for benchmark problems and a real-world problem are presented and discussed. The experiments have shown that the proposed approach can be used for designing new selection operators that outperform standard selection operators on average.

Номера страниц: 13-24

• Sopov E. (Reshetnev Siberian State University of Science and Technology)
• Semenkin E. (Reshetnev Siberian State University of Science and Technology)

• Ядро РИНЦ (eLIBRARY.RU)