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dc.date.accessioned 2020-02-20T16:46:42Z
dc.date.available 2020-02-20T16:46:42Z
dc.date.issued 2019
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/89504
dc.description.abstract This paper presents a MILP-based decomposition algorithm for solving large-scale scheduling problems with assembly operations in flexible flow shop environments. First, a rigorous mixed-integer linear (MILP) formulation based on the general precedence notion is developed for the problem under study. Then, the MILP model is embedded within a decomposition algorithm in order to accelerate the resolution of large-size industrial problems. The proposed solution approach is tested on several examples derived from a real-world case study arising in a shipbuilding company. en
dc.format.extent 64-75 es
dc.language en es
dc.subject Flexible flow shop es
dc.subject Scheduling problem es
dc.subject Assembly operations es
dc.subject MILP model es
dc.subject Decomposition strategy es
dc.title An Efficient MILP-Based Decomposition Strategy for Solving Large-Scale Scheduling Problems en
dc.type Objeto de conferencia es
sedici.identifier.issn 2618-3277 es
sedici.creator.person Basán, Natalia P. es
sedici.creator.person Cóccola, Mariana E. es
sedici.creator.person Méndez, Carlos A. es
sedici.subject.materias Ciencias Informáticas es
sedici.description.fulltext true es
mods.originInfo.place Sociedad Argentina de Informática e Investigación Operativa es
sedici.subtype Objeto de conferencia es
sedici.rights.license Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0)
sedici.rights.uri http://creativecommons.org/licenses/by-sa/3.0/
sedici.date.exposure 2019-09
sedici.relation.event I Simposio Argentino de Informática Industrial e Investigación Operativa (SIIIO 2019) - JAIIO 48 (Salta) es
sedici.description.peerReview peer-review es


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Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0)