Genetic programming with individual simplification policy for dynamic multi-flexible job shop scheduling problem
QIU Jia-long
GONG Wen-yin
ZHANG Guo-hui
LU Chao
Abstract：Studying the dynamic flexible job-shop scheduling problem(DFJSP)is of great significance for effectively controlling production processes and enhancing enterprises' economic profitability.Existing studies mostly only consider machine selection flexibility and dynamic production scenarios;however,a more complex issue of flexible process sequence exists in practical production.Specifically,in scenarios like customized equipment manufacturing,job processing opera-tions can be divided into several groups according to process requirements.There are no mandatory processing sequence constraints apply to operations within the same group,whereas strict processing sequence constraints must be followed between different groups.The introduction of this flexible process sequence significantly increases the complexity of the problem's search space,leading to a substantial extension of solution time.Therefore,by integrating the practical produc-tion needs of customized equipment manufacturing workshops,this paper comprehensively considers machine selection flexibility,flexible process sequence,and the dynamic characteristic of new job arrivals,and proposes the dynamic multi-flexible job-shop scheduling problem(DMFJSP)with the optimization objective of minimizing the average flow time.To solve this problem,a genetic programming(GP)method based on individual simplification is proposed which analyzes the structural complexity of individuals by introducing dynamic terminal node frequency,and sets a penalty function during the fitness evaluation stage to guide population evolution—ultimately simplifying individual structures and reducing GP training time.To verify the effectiveness of the proposed method,tests are conducted under three different production sce-narios.The results demonstrate that the method can significantly shorten computation time while ensuring solution quality;when addressing larger-scale and more complex problems,it exhibits fast convergence and can obtain satisfactory solutions within a reasonable time frame.
Keywords：dynamic flexible job shop scheduling problemflexible process sequencegenetic programming
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：11( 2587-2597 )