Tabassum, Muhammad FarhanAkgul, AliAkram, SanaHassan, SaadiaSamanQudus, AyeshaKarim, Rabia2024-12-242024-12-2420220031-89491402-4896https://doi.org/10.1088/1402-4896/ac41echttps://hdl.handle.net/20.500.12604/7079It is very necessary and applicable to optimize all disciplines. In practical engineering problems the optimization has been a significant component. This article presents the hybrid approach named as differential gradient evolution plus (DGE+) algorithm which is the combination of differential evolution gorithm and gradient evolution (GE) algorithm. DE was used to diversify and GE was used for intensification with a perfect equilibrium between exploration and exploitation with an improvised distribution of dynamic probability and offers a new shake-off approach to prevent premature convergence to local optimum. To describe the success, the proposed algorithm is compared to modern meta-heuristics. To see the accuracy, robustness, and reliability of DGE+ it has been implemented on eight complex practical engineering problems named as: pressure vessel, belleville spring, tension/compression spring, three-bar truss, welded beam, speed reducer, gear train and rolling element bearing design problem, the results revealed that DGE+ algorithm can deliver highly efficient, competitive and promising results.eninfo:eu-repo/semantics/closedAccessmeta-heuristicshybridizationdifferential evolutiongradient evolutionpractical engineering designsArticle971Q2WOS:000740837400001Q12-s2.0-8512400160210.1088/1402-4896/ac41ec