New three-level recursive differential grouping method for large-scale optimization problems
LI Fei
LIU Xiang
XU Hong-bin
LIU Jian-chang
Abstract：The cooperative coevolution algorithm performs well in solving large-scale global optimization problems.The core idea of cooperative coevolution is to utilize a divide-and-conquer strategy for decomposing high-dimensional problems into multiple subproblems,which are then processed individually and separately.However,existing decomposi-tion methods typically require significant computational cost to obtain accurate variable grouping.To address this issue,a novel three-level recursive differential grouping strategy(NTRDG)is proposed in this paper,which simplifies the group-ing process by utilizing historical information in recursive interaction detection and avoids the detection of relationships among certain sets,leading to a lower computational cost without sacrificing grouping accuracy.Simulation results demon-strate that compared to four existing methods,NTRDG exhibits a stronger competitiveness in solving large-scale global optimization problems.
Keywords：global optimizationcooperative coevolutiondecomposition methodsthree-level recursive differential groupingrecursive search
Publication Date：2024-04-28
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：10( 691-700 )