TY - GEN
T1 - Flexible Job-Shop Scheduling with Setups and Variable Sublots
AU - Yan, Ge
AU - Aimin, Wang
AU - Zijin, Zhao
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/1
Y1 - 2020/1
N2 - In the flexible job shop scheduling problem (FJSP), jobs are always processed in batches. Considering the scheduling objective of minimising the maximum completion time (Cmax), splitting each job into sublots is necessary. However, if the sublots are too small, the time loss caused by the frequent change of jobs on the same machine will increase. Therefore, all processes involved in the FJSP must be split into sublots considering efficiency. This paper proposes a mathematical model with the objective function of minimising the maximum completion time Cmax and the research objective of providing process-level batches and a scheduling technology for the FJSP with setups and sublots. A genetic algorithm is applied to optimise the allocation of the process-level batches on the machines. Finally, a software system for algorithm verification that verifies the validity of our proposed algorithm was developed.
AB - In the flexible job shop scheduling problem (FJSP), jobs are always processed in batches. Considering the scheduling objective of minimising the maximum completion time (Cmax), splitting each job into sublots is necessary. However, if the sublots are too small, the time loss caused by the frequent change of jobs on the same machine will increase. Therefore, all processes involved in the FJSP must be split into sublots considering efficiency. This paper proposes a mathematical model with the objective function of minimising the maximum completion time Cmax and the research objective of providing process-level batches and a scheduling technology for the FJSP with setups and sublots. A genetic algorithm is applied to optimise the allocation of the process-level batches on the machines. Finally, a software system for algorithm verification that verifies the validity of our proposed algorithm was developed.
KW - Sublots
KW - designed efficiency factor
KW - flexible job shop scheduling problem
KW - genetic algorithm
KW - process-level batches
UR - http://www.scopus.com/inward/record.url?scp=85083204547&partnerID=8YFLogxK
U2 - 10.1109/ICMIMT49010.2020.9041218
DO - 10.1109/ICMIMT49010.2020.9041218
M3 - Conference contribution
AN - SCOPUS:85083204547
T3 - Proceedings of 2020 IEEE 11th International Conference on Mechanical and Intelligent Manufacturing Technologies, ICMIMT 2020
SP - 187
EP - 192
BT - Proceedings of 2020 IEEE 11th International Conference on Mechanical and Intelligent Manufacturing Technologies, ICMIMT 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 11th IEEE International Conference on Mechanical and Intelligent Manufacturing Technologies, ICMIMT 2020
Y2 - 20 January 2020 through 22 January 2020
ER -