dc.creatorTroncoso, JJ
dc.creatorGarrido, RA
dc.date.accessioned2024-01-10T12:39:03Z
dc.date.accessioned2024-05-02T18:34:49Z
dc.date.available2024-01-10T12:39:03Z
dc.date.available2024-05-02T18:34:49Z
dc.date.created2024-01-10T12:39:03Z
dc.date.issued2005
dc.identifier10.1016/j.forpol.2003.12.002
dc.identifier1872-7050
dc.identifier1389-9341
dc.identifierhttps://doi.org/10.1016/j.forpol.2003.12.002
dc.identifierhttps://repositorio.uc.cl/handle/11534/77139
dc.identifierWOS:000229008600013
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/9270660
dc.description.abstractThis article presents a mathematical model for the problem of production and logistics in the forest industry. Specifically, a dynamic model of mixed-integer programming was formulated to solve three common problems in the forest sector: forest production, forest facilities location and forest freight distribution. The implemented mathematical model allows the strategic selection of the optimal location and size of a forest facility, in addition to the identification of the production levels and freight flows that will be generated in the considered planning horizon. A practical application of the model was carried out, validating its utility in the location of a sawmill. The model was optimally solved using LINGO, which also allowed to evaluate its response capacity in relation to changes in information considered in the initial planning, as well as the comparison of the decisions and the solution times for different scenarios such as demand, transportation costs, timber prices and yields of the sawn process. (c) 2004 Elsevier B.V. All rights reserved.
dc.languageen
dc.publisherELSEVIER SCIENCE BV
dc.rightsacceso restringido
dc.subjectforest planning
dc.subjectproduction and logistics
dc.subjectplant location problem
dc.subjectmixed-integer programming
dc.subjectLANDING LOCATION
dc.subjectUNIFORM TERRAIN
dc.subjectPLANT LOCATION
dc.subjectOPERATIONS
dc.subjectMODEL
dc.subjectSIZE
dc.subjectFLAT
dc.titleForestry production and logistics planning: an analysis using mixed-integer programming
dc.typeartículo


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