期刊名称：An International Journal of Optimization and Control: Theories & Applications (IJOCTA)
印刷版ISSN：2146-5703
出版年度：2021
卷号：11
期号：2
页码：158-177
DOI：10.11121/ijocta.01.2021.001077
语种：English
出版社：An International Journal of Optimization and Control: Theories & Applications (IJOCTA)
摘要：Optimization for all disciplines is very important and applicable. Optimization has played a key role in practical engineering problems. A novel hybrid meta-heuristic optimization algorithm that is based on Differential Evolution (DE), Gradient Evolution (GE) and Jumping Technique named Differential Gradient Evolution Plus (DGE+) are presented in this paper. The proposed algorithm hybridizes the above-mentioned algorithms with the help of an improvised dynamic probability distribution, additionally provides a new shake off method to avoid premature convergence towards local minima. To evaluate the efficiency, robustness, and reliability of DGE+ it has been applied on seven benchmark constraint problems, the results of comparison revealed that the proposed algorithm can provide very compact, competitive and promising performance.
