TY - GEN
T1 - Job Shop Scheduling Problem with Job Sizes and Inventories
AU - Xinyi, Shen
AU - Aimin, Wang
AU - Yan, Ge
AU - Jieran, Ye
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/1
Y1 - 2020/1
N2 - In order to satisfy better the actual situation of modern manufacturing enterprise workshop scheduling and the need of lean production, this paper considers the job shop scheduling problem with inventories and batch size of each job. In this problem, for some jobs, if the inventory can meet the demand, no further processing is required. Therefore, the actual processing batch size of a job is its demand size minus the inventory size of the job. Job sizes influence the starting time of operations. With the objective of minimizing the makespan of all jobs, a mixed integer programming model is established. A genetic algorithm is used to solve the proposed model. Finally, a program was developed with the actual data, job sizes, inventories and the job sizes of starting operations to verify the feasibility and effectiveness of the algorithm. The result shows that the algorithm achieves satisfactory results in all indexes mentioned above.
AB - In order to satisfy better the actual situation of modern manufacturing enterprise workshop scheduling and the need of lean production, this paper considers the job shop scheduling problem with inventories and batch size of each job. In this problem, for some jobs, if the inventory can meet the demand, no further processing is required. Therefore, the actual processing batch size of a job is its demand size minus the inventory size of the job. Job sizes influence the starting time of operations. With the objective of minimizing the makespan of all jobs, a mixed integer programming model is established. A genetic algorithm is used to solve the proposed model. Finally, a program was developed with the actual data, job sizes, inventories and the job sizes of starting operations to verify the feasibility and effectiveness of the algorithm. The result shows that the algorithm achieves satisfactory results in all indexes mentioned above.
KW - genetic algorithm
KW - inventories
KW - job sizes
KW - job-shop scheduling problem
UR - http://www.scopus.com/inward/record.url?scp=85083228903&partnerID=8YFLogxK
U2 - 10.1109/ICMIMT49010.2020.9041174
DO - 10.1109/ICMIMT49010.2020.9041174
M3 - Conference contribution
AN - SCOPUS:85083228903
T3 - Proceedings of 2020 IEEE 11th International Conference on Mechanical and Intelligent Manufacturing Technologies, ICMIMT 2020
SP - 202
EP - 206
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 -