Improved multifactorial differential evolution algorithm for copper ingredient optimization
ZHANG Xue-rui
HAN Zhong-yang
ZHAO Jun
WANG Wei
Abstract：As a key foundation of the entire production process of copper products,ingredient plan is directly related to the continuous stability of the subsequent process and the economic benefits of the enterprise.Considering the unsatisfied resource utilization of ingredient plans provided by existing methods,an ingredient optimization model with the objective of maximizing resource utilization and ingredient consistency is established.Then,an improved multifactorial differential evolution algorithm is proposed.To solve premature convergence and infeasible solutions caused by complex constraints in the traditional multifactorial differential evolution algorithm,the improved algorithm first designs a mutation strategy based on the sine cosine algorithm to balance cross task knowledge transfer,global search,and local development capabilities of the algorithm.Secondly,the Levy optimal perturbation strategy is introduced to improve the diversity of solutions,and prevent the algorithm from getting stuck in local optima.In addition,a repair strategy for infeasible solutions with lower computational cost is proposed to ensure search efficiency.Finally,simulation experiments based on real data from a domestic copper industry and multitask benchmark problems demonstrate that compared with other methods,the model and method proposed in this paper can significantly improve the resource utilization rate and consistency of ingredient plan,providing good support for stable production in the copper industry.And the proposed algorithm exhibits good stability in complex multitask benchmark problems.
Keywords：ingredient optimizationevolutionary algorithmmultitask optimizationconstraint handling
Publication Date：2025-12-30
Online Publishing Date：2026-03-05(First online date of this platform, not the publication date of the document)
Pages：12( 2557-2568 )