Tabassum, Muhammad FarhanAkram, SanaHassan, SaadiaKarim, RabiaNaik, Parvaiz AhmadFarman, MuhammadYavuz, Mehmet2024-02-232024-02-2320212146-09572146-5703https://doi.org/10.11121/ijocta.01.2021.001077https://hdl.handle.net/20.500.12452/14056Optimization 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.eninfo:eu-repo/semantics/openAccessMeta-Heuristic AlgorithmsHybridizationDifferential EvolutionGradient EvolutionConstraint Optimization ProblemsArticle1121581772-s2.0-85123999822Q3WOS:00088497320000510.11121/ijocta.01.2021.001077