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Machine-part cell formation problems with constraint programming
dc.contributor.author | Sotoyz R. | |
dc.contributor.author | Crawford B. | |
dc.contributor.author | Almonacid B. | |
dc.contributor.author | Paredes F. | |
dc.contributor.author | Loyola E. | |
dc.date.accessioned | 2020-09-02T22:28:46Z | |
dc.date.available | 2020-09-02T22:28:46Z | |
dc.date.issued | 2016 | |
dc.identifier | 10.1109/SCCC.2015.7416567 | |
dc.identifier.citation | 2016-February, , - | |
dc.identifier.issn | 15224902 | |
dc.identifier.uri | https://hdl.handle.net/20.500.12728/6341 | |
dc.description | Machine-Part Cell Formation consists on organizing a plant as a set of cells, each one of them processing machines containing different part types. In recent years, different techniques have been used to solve this problem ranging from exact to approximate methods. This paper focuses on solving new instances of this problem for which no optimal value exists by using the classic Boctor's mathematical model. We employ constraint programming as the underlying solving technique illustrating that global optimums are achieved for the whole set of tested instances. © 2015 IEEE. | |
dc.language.iso | en | |
dc.publisher | IEEE Computer Society | |
dc.subject | Constraint Programming | |
dc.subject | Machine-Part Cell Formation | |
dc.subject | Optimization | |
dc.subject | Cells | |
dc.subject | Cellular manufacturing | |
dc.subject | Computer programming | |
dc.subject | Constraint theory | |
dc.subject | Cytology | |
dc.subject | Machinery | |
dc.subject | Optimization | |
dc.subject | Approximate methods | |
dc.subject | Cell formation | |
dc.subject | Cell formation problem | |
dc.subject | Constraint programming | |
dc.subject | Global optimum | |
dc.subject | Optimal values | |
dc.subject | Processing machines | |
dc.subject | Problem solving | |
dc.title | Machine-part cell formation problems with constraint programming | |
dc.type | Conference Paper |