Тип публикации: статья из журнала

Год издания: 2018

Ключевые слова: restart meta-heuristic, genetic algorithm, multi-objective optimization, benchmark problems, performance improvement

Аннотация: We introduce a generic scheme of restarting for multi-objective genetic algorithms and demonstrate that the use of a restart operator leads to a significant improvement in solution quality due to its tendency to explore different regions of a search space and get uniformly distributed points along a true front. The proposed scheme Показать полностьюof restarting tells us when to restart an algorithm and how to generate a new population based on previously found solutions. This operator is algorithmindependent, which we show by incorporating it into three multi-objective genetic algorithms based on different heuristics.

Журнал: International Journal on Information Technologies and Security

Выпуск журнала: Т. 10, № 2

Номера страниц: 101-110

ISSN журнала: 13138251

Место издания: Sofia

• Brester C.C. (Reshetnev Siberian State University of Science and Technology)
• Ryzhikov I.I. (Reshetnev Siberian State University of Science and Technology)
• Semenkina O.O. (Reshetnev Siberian State University of Science and Technology)

• Ядро РИНЦ (eLIBRARY.RU)