Tuning of the metaheuristic variable neighborhood search for a forest planning problem

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dc.creatorCarlos Alberto Araújo Júnior
dc.creatorJoão Batista Mendes
dc.creatorAdriana Leandra de Assis
dc.creatorChristian Dias Cabacinha
dc.creatorJonathan James Stocks
dc.creatorLiniker Fernandes da Silva
dc.creatorHelio Garcia Leite
dc.date.accessioned2022-07-14T15:12:00Z
dc.date.accessioned2025-09-08T23:53:54Z
dc.date.available2022-07-14T15:12:00Z
dc.date.issued2018
dc.description.sponsorshipCNPq - Conselho Nacional de Desenvolvimento Científico e Tecnológico
dc.description.sponsorshipFAPEMIG - Fundação de Amparo à Pesquisa do Estado de Minas Gerais
dc.identifier.doihttps://doi.org/10.1590/01047760201824032538
dc.identifier.issn0104-7760
dc.identifier.urihttps://hdl.handle.net/1843/43264
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.relation.ispartofCerne
dc.rightsAcesso Aberto
dc.subjectPesquisa operacional
dc.subjectInteligência artificial
dc.subjectFlorestas – Administração
dc.titleTuning of the metaheuristic variable neighborhood search for a forest planning problem
dc.typeArtigo de periódico
local.citation.epage268
local.citation.issue3
local.citation.spage259
local.citation.volume24
local.description.resumoIn forest science it is important evaluate new technologies from computational science. This work aimed to test a different kind of metaheuristic called Variable Neighborhood Search in a forest planning problem. The management total area has 4.210 ha distributed in 120 stands in ages between 1 and 6 years old and site index since 22 m to 31 m. The problem was modelled considering the maximization of the net present value subject to the restrictions: annual cut volume between 140.000 m³ and 160.000 m³, harvester ages equal to 5, 6 or 7 years, and the impossibility of division of the management unity at harvester time. It was evaluated different settings for the Variable Neighborhood Search, varying the quantity of neighbours, the neighbourhood structure and number or generations. 30 repetitions were performed for each setting. The results were compared to the one obtained from integer linear programming and linear programming. The integer linear programming considered the best solution obtained after 1 hour of processing. The best setting to the Variable Neighborhood Search was 100 neighbours, a neighbourhood structure with changes in 1%, 2%, 3% and 4% of prescriptions and 500 iterations. The results shown by the Variable Neighborhood Search was 2,77% worse than one obtained by the integer linear programming with 1 hours of processing, and 2,84% worse than the linear programming. It is possible to conclude that the presented metaheuristic can be used satisfactorily in a resolution of forest scheduling problem when the best parameters are chosen.
local.identifier.orcidhttps://orcid.org/0000-0003-0909-8633
local.identifier.orcidhttps://orcid.org/0000-0002-8148-083X
local.publisher.countryBrasil
local.publisher.departmentICA - INSTITUTO DE CIÊNCIAS AGRÁRIAS
local.publisher.initialsUFMG
local.url.externahttps://www.scielo.br/j/cerne/a/5S5kMdwzJZ9cQ7Bt5HJ3DXp/?format=pdf

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