Forestry production and logistics planning: an analysis using mixed-integer programming [An article from: Forest Policy and Economics]
Book Details
Author(s)J.J. Troncoso, R.A. Garrido
PublisherElsevier
ISBN / ASINB000RR4OBC
ISBN-13978B000RR4OB0
AvailabilityAvailable for download now
MarketplaceUnited States 🇺🇸
Description
This digital document is a journal article from Forest Policy and Economics, published by Elsevier in 2005. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.
Description:
This 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.
Description:
This 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.
