TY - JOUR
T1 - A hyperheuristic approach for intercell scheduling with single processing machines and batch processing machines
AU - Li, Dongni
AU - Li, Miao
AU - Meng, Xianwen
AU - Tian, Yunna
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2015/2/1
Y1 - 2015/2/1
N2 - Intercell transfers in cellular manufacturing systems disrupt the philosophy of creating independent cells, but are essential for enterprises to reduce production costs. The problem of intercell scheduling with single processing machines and batch processing machines is considered in this paper, which involves an assignment subproblem, a sequencing subproblem, and a batch formation subproblem. An ant colony optimization (ACO)-based hyperheuristic (ABH) is developed in this paper, searching assignment rules for parts, sequencing rules for single processing machines, and batch formation rules for batch processing machines, simultaneously, and then using the obtained combinatorial rules to generate scheduling solutions. Computational results show that ABH is an effective and significantly efficient approach to provide near-optimum solutions even when CPLEX shows poor performance, and as compared to genetic algorithm that is widely used in hyperheuristics, ABH has better performance with respect to the problem addressed in this paper.
AB - Intercell transfers in cellular manufacturing systems disrupt the philosophy of creating independent cells, but are essential for enterprises to reduce production costs. The problem of intercell scheduling with single processing machines and batch processing machines is considered in this paper, which involves an assignment subproblem, a sequencing subproblem, and a batch formation subproblem. An ant colony optimization (ACO)-based hyperheuristic (ABH) is developed in this paper, searching assignment rules for parts, sequencing rules for single processing machines, and batch formation rules for batch processing machines, simultaneously, and then using the obtained combinatorial rules to generate scheduling solutions. Computational results show that ABH is an effective and significantly efficient approach to provide near-optimum solutions even when CPLEX shows poor performance, and as compared to genetic algorithm that is widely used in hyperheuristics, ABH has better performance with respect to the problem addressed in this paper.
KW - Management decision-making
KW - manufacturing scheduling
KW - optimization methods
KW - production management
UR - http://www.scopus.com/inward/record.url?scp=84921418135&partnerID=8YFLogxK
U2 - 10.1109/TSMC.2014.2332443
DO - 10.1109/TSMC.2014.2332443
M3 - Article
AN - SCOPUS:84921418135
SN - 2168-2216
VL - 45
SP - 315
EP - 325
JO - IEEE Transactions on Systems, Man, and Cybernetics: Systems
JF - IEEE Transactions on Systems, Man, and Cybernetics: Systems
IS - 2
M1 - 6871417
ER -