An iterated greedy algorithm based on population evolution for distributed blocking flowshop scheduling with balanced energy costs criterion
HAN Xue
WANG Yu-ting
HAN Yu-yan
LI Jun-qing
Abstract：Based on the classical distributed flowshop scheduling problem,this paper constructs the mixed linear in-teger programming mode(MILP)of distributed blocking flowshop scheduling problem with sequence-dependent setup time(DBFSP_SDST),and the optimization objective is to balance the energy consumption cost of each factory.To tack-le this problem,an iterated greedy algorithm based on the population evolution(PEIG)is proposed.In PEIG,firstly,a problem-specific heuristic is well designed based on the blocking constraint and multiple factories model.Secondly,for the advantages and disadvantages of the traditional IG algorithm,the local search strategies based on the population operation,the multiple neighborhood search structures,and the cross-factory destruction-reconstruction strategy are proposed to fur-ther balance the global exploration and exploitation abilities of the proposed algorithm.The 270 test instances numerical simulations and statistical comparison with four representative algorithms show that the proposed algorithm has superior performance and can provide a better scheduling scheme for medium and large-scale DBFSP_SDST than the compared algorithms.
Keywords：distributedblocking flowshop schedulingenergy consumption costlocal search strategy based on popu-lationiterated greedy algorithm
Publication Date：2024-06-28
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：9( 1147-1155 )