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Logic-based Benders decomposition method for the seru scheduling problem with sequence-dependent setup time and DeJong’s learning effect
- Source :
- European Journal of Operational Research. 297:866-877
- Publication Year :
- 2022
- Publisher :
- Elsevier BV, 2022.
-
Abstract
- This paper concentrates on the scheduling problem in seru production system (SPS), where seru is a successful new-type production mode arising from the Japanese labor-intensive electronic assembly industry. Motivated by the practical situations, the sequence-dependent setup time and DeJong’s learning effect are considered in seru scheduling problems, and the objective is to minimize the makespan. The seru scheduling problem is formulated as a mixed-integer programming (MIP), and then reformulated to a set partitioning master problem and some independent subproblems by employing the logic-based Benders decomposition (LBBD) method. Subsequently, the set partitioning master problem is used to assign jobs to serus of SPS, and the subproblems are applied to find the optimal schedules in each seru given the assignment of the master problem. Finally, computational studies are made, and results indicate that the LBBD method is able to return high-quality schedules for solving seru scheduling problems.
- Subjects :
- 050210 logistics & transportation
Mathematical optimization
021103 operations research
Information Systems and Management
Sequence-dependent setup
General Computer Science
Job shop scheduling
Computer science
05 social sciences
0211 other engineering and technologies
Scheduling (production processes)
02 engineering and technology
Management Science and Operations Research
Benders' decomposition
Industrial and Manufacturing Engineering
Learning effect
Set (abstract data type)
Modeling and Simulation
0502 economics and business
Production (computer science)
Benders decomposition method
Subjects
Details
- ISSN :
- 03772217
- Volume :
- 297
- Database :
- OpenAIRE
- Journal :
- European Journal of Operational Research
- Accession number :
- edsair.doi...........2faabb32673503b6fe4536307e306ff5