Road network, landing location, and routing optimization for forest smallholders landscapes
We present two mixed integer linear programming (MILP) formulations for a well‐known integrated network, timber landing location, and routing problem that arises in forest management. The models seek to jointly optimize the construction and maintenance schedule of forest road networks with landing s...
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Veröffentlicht in: | International transactions in operational research 2025-03, Vol.32 (2), p.888-917 |
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creator | Constantino, Miguel F. Mesquita, Marta Marques, Susete Tóth, Sándor F. Borges, José G. |
description | We present two mixed integer linear programming (MILP) formulations for a well‐known integrated network, timber landing location, and routing problem that arises in forest management. The models seek to jointly optimize the construction and maintenance schedule of forest road networks with landing site selection and transportation routing for timber production. This problem is, in general, difficult to solve as it contains the so‐called fixed charge network flow problem, which is known to be NP‐hard. One of the proposed MILP formulations considers 3‐index continuous variables to represent timber flows on road segments in each period. The presence of Big‐M constraints leads to weak linear relaxation bounds. Disaggregating flow variables, according to timber origin, results in a novel 4‐index formulation with very tight linear relaxation bounds. Nevertheless, the number of variables increases prohibitively. This research makes use of spatial constraints common to Smallholding Forested Landscapes to develop a solution approach that reduces the number of flow variables in the new 4‐index model. Results from a real‐world case study located in Northwest Portugal show that, with the 4‐index formulation, the proposed solution approach makes it possible to obtain optimal solutions in a short computational time. |
doi_str_mv | 10.1111/itor.13485 |
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The models seek to jointly optimize the construction and maintenance schedule of forest road networks with landing site selection and transportation routing for timber production. This problem is, in general, difficult to solve as it contains the so‐called fixed charge network flow problem, which is known to be NP‐hard. One of the proposed MILP formulations considers 3‐index continuous variables to represent timber flows on road segments in each period. The presence of Big‐M constraints leads to weak linear relaxation bounds. Disaggregating flow variables, according to timber origin, results in a novel 4‐index formulation with very tight linear relaxation bounds. Nevertheless, the number of variables increases prohibitively. This research makes use of spatial constraints common to Smallholding Forested Landscapes to develop a solution approach that reduces the number of flow variables in the new 4‐index model. Results from a real‐world case study located in Northwest Portugal show that, with the 4‐index formulation, the proposed solution approach makes it possible to obtain optimal solutions in a short computational time.</description><identifier>ISSN: 0969-6016</identifier><identifier>EISSN: 1475-3995</identifier><identifier>DOI: 10.1111/itor.13485</identifier><language>eng</language><publisher>Oxford: Blackwell Publishing Ltd</publisher><subject>Computing time ; Constraints ; Forest management ; forest road network optimization ; Integer programming ; Landing sites ; Linear programming ; Mixed integer ; mixed integer linear programming ; Optimization ; OR in natural resources ; Real variables ; Road maintenance ; Routing ; Site selection ; Timber construction ; Transportation networks</subject><ispartof>International transactions in operational research, 2025-03, Vol.32 (2), p.888-917</ispartof><rights>2024 International Federation of Operational Research Societies.</rights><rights>2025 The Authors.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c1905-80f835a696f2315e660817d7cf6ad50f968c24d764cf6cde4f8341e50bb3b5623</cites><orcidid>0000-0001-7550-2740</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Fitor.13485$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Fitor.13485$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>315,781,785,1418,27929,27930,45579,45580</link.rule.ids></links><search><creatorcontrib>Constantino, Miguel F.</creatorcontrib><creatorcontrib>Mesquita, Marta</creatorcontrib><creatorcontrib>Marques, Susete</creatorcontrib><creatorcontrib>Tóth, Sándor F.</creatorcontrib><creatorcontrib>Borges, José G.</creatorcontrib><title>Road network, landing location, and routing optimization for forest smallholders landscapes</title><title>International transactions in operational research</title><description>We present two mixed integer linear programming (MILP) formulations for a well‐known integrated network, timber landing location, and routing problem that arises in forest management. The models seek to jointly optimize the construction and maintenance schedule of forest road networks with landing site selection and transportation routing for timber production. This problem is, in general, difficult to solve as it contains the so‐called fixed charge network flow problem, which is known to be NP‐hard. One of the proposed MILP formulations considers 3‐index continuous variables to represent timber flows on road segments in each period. The presence of Big‐M constraints leads to weak linear relaxation bounds. Disaggregating flow variables, according to timber origin, results in a novel 4‐index formulation with very tight linear relaxation bounds. Nevertheless, the number of variables increases prohibitively. This research makes use of spatial constraints common to Smallholding Forested Landscapes to develop a solution approach that reduces the number of flow variables in the new 4‐index model. Results from a real‐world case study located in Northwest Portugal show that, with the 4‐index formulation, the proposed solution approach makes it possible to obtain optimal solutions in a short computational time.</description><subject>Computing time</subject><subject>Constraints</subject><subject>Forest management</subject><subject>forest road network optimization</subject><subject>Integer programming</subject><subject>Landing sites</subject><subject>Linear programming</subject><subject>Mixed integer</subject><subject>mixed integer linear programming</subject><subject>Optimization</subject><subject>OR in natural resources</subject><subject>Real variables</subject><subject>Road maintenance</subject><subject>Routing</subject><subject>Site selection</subject><subject>Timber construction</subject><subject>Transportation networks</subject><issn>0969-6016</issn><issn>1475-3995</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2025</creationdate><recordtype>article</recordtype><recordid>eNp9kMtKAzEUhoMoWKsbnyDgTjo1mZlkJkspXgqFQqkrFyHNRVPTyZhMKfXpzXRce-Bw4D_fufADcIvRFKd4sJ0PU1yUNTkDI1xWJCsYI-dghBhlGUWYXoKrGLcIIUxwNQLvKy8UbHR38OFrAp1olG0-oPNSdNY3E5gEGPy-61XfdnZnf04daHzoU8cOxp1w7tM7pUM8rYhStDpegwsjXNQ3f3UM3p6f1rPXbLF8mc8eF5nEDJGsRqYuiKCMmrzARFOKalypShoqFEGG0VrmpapomRSpdJnwEmuCNptiQ2hejMHdsLcN_nufHuJbvw9NOsmLZAqp8hz31P1AyeBjDNrwNtidCEeOEe_N4715_GRegvEAH6zTx39IPl8vV8PML4vWcrg</recordid><startdate>202503</startdate><enddate>202503</enddate><creator>Constantino, Miguel F.</creator><creator>Mesquita, Marta</creator><creator>Marques, Susete</creator><creator>Tóth, Sándor F.</creator><creator>Borges, José G.</creator><general>Blackwell Publishing Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0001-7550-2740</orcidid></search><sort><creationdate>202503</creationdate><title>Road network, landing location, and routing optimization for forest smallholders landscapes</title><author>Constantino, Miguel F. ; Mesquita, Marta ; Marques, Susete ; Tóth, Sándor F. ; Borges, José G.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c1905-80f835a696f2315e660817d7cf6ad50f968c24d764cf6cde4f8341e50bb3b5623</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2025</creationdate><topic>Computing time</topic><topic>Constraints</topic><topic>Forest management</topic><topic>forest road network optimization</topic><topic>Integer programming</topic><topic>Landing sites</topic><topic>Linear programming</topic><topic>Mixed integer</topic><topic>mixed integer linear programming</topic><topic>Optimization</topic><topic>OR in natural resources</topic><topic>Real variables</topic><topic>Road maintenance</topic><topic>Routing</topic><topic>Site selection</topic><topic>Timber construction</topic><topic>Transportation networks</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Constantino, Miguel F.</creatorcontrib><creatorcontrib>Mesquita, Marta</creatorcontrib><creatorcontrib>Marques, Susete</creatorcontrib><creatorcontrib>Tóth, Sándor F.</creatorcontrib><creatorcontrib>Borges, José G.</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>International transactions in operational research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Constantino, Miguel F.</au><au>Mesquita, Marta</au><au>Marques, Susete</au><au>Tóth, Sándor F.</au><au>Borges, José G.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Road network, landing location, and routing optimization for forest smallholders landscapes</atitle><jtitle>International transactions in operational research</jtitle><date>2025-03</date><risdate>2025</risdate><volume>32</volume><issue>2</issue><spage>888</spage><epage>917</epage><pages>888-917</pages><issn>0969-6016</issn><eissn>1475-3995</eissn><abstract>We present two mixed integer linear programming (MILP) formulations for a well‐known integrated network, timber landing location, and routing problem that arises in forest management. The models seek to jointly optimize the construction and maintenance schedule of forest road networks with landing site selection and transportation routing for timber production. This problem is, in general, difficult to solve as it contains the so‐called fixed charge network flow problem, which is known to be NP‐hard. One of the proposed MILP formulations considers 3‐index continuous variables to represent timber flows on road segments in each period. The presence of Big‐M constraints leads to weak linear relaxation bounds. Disaggregating flow variables, according to timber origin, results in a novel 4‐index formulation with very tight linear relaxation bounds. Nevertheless, the number of variables increases prohibitively. This research makes use of spatial constraints common to Smallholding Forested Landscapes to develop a solution approach that reduces the number of flow variables in the new 4‐index model. Results from a real‐world case study located in Northwest Portugal show that, with the 4‐index formulation, the proposed solution approach makes it possible to obtain optimal solutions in a short computational time.</abstract><cop>Oxford</cop><pub>Blackwell Publishing Ltd</pub><doi>10.1111/itor.13485</doi><tpages>30</tpages><orcidid>https://orcid.org/0000-0001-7550-2740</orcidid></addata></record> |
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subjects | Computing time Constraints Forest management forest road network optimization Integer programming Landing sites Linear programming Mixed integer mixed integer linear programming Optimization OR in natural resources Real variables Road maintenance Routing Site selection Timber construction Transportation networks |
title | Road network, landing location, and routing optimization for forest smallholders landscapes |
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