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A hybrid dynamic programming for solving a mixed-model sequencing problem with production mix restriction and free interruptions

Author
Bautista, J.; Cano, A.; Alfaro, R.
Type of activity
Journal article
Journal
Progress in Artificial Intelligence
Date of publication
2017-03
Volume
6
Number
1
First page
27
Last page
39
DOI
https://doi.org/10.1007/s13748-016-0101-5 Open in new window
Project funding
Human factor and uncertainty on the sequencing and balancing mixed model lines
Repository
http://hdl.handle.net/2117/89599 Open in new window
URL
http://link.springer.com/journal/13748 Open in new window
Abstract
In this article, we propose a hybrid procedure based on bounded dynamic programming assisted by linear programming to solve the mixed-model sequencing problem with workload minimization with serial workstations, free interruption of the operations and with production mix restrictions. We performed a computational experiment with 23 instances related to a case study of the Nissan powertrain plant located in Barcelona. The results of our proposal are compared with those obtained by mixed integer l...
Citation
Bautista, J., Cano, A., Alfaro, R. A hybrid dynamic programming for solving a mixed-model sequencing problem with production mix restriction and free interruptions. "Progress in Artificial Intelligence", 30 Agost 2016, vol. 5, núm. August 2016, p. 1-13.
Keywords
Dynamic programming, Hybrid metaheuristics, Industrial application, Mixed integer linear programming, Mixed-model sequencing
Group of research
OPE-PROTHIUS -

Participants