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Autore principale: Carlos Alberto Araújo Júnior
Natura: Artículo científico
Lingua:en
Pubblicazione: Universidade Federal de Lavras 2018
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Accesso online:https://www.redalyc.org/articulo.oa?id=74460167012
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_version_ 1866568092028502016
author Carlos Alberto Araújo Júnior
author_facet Carlos Alberto Araújo Júnior
contents TUNING OF THE METAHEURISTIC VARIABLE NEIGHBORHOOD SEARCH FOR A FOREST PLANNING PROBLEM Carlos Alberto Araújo Júnior João Batista Mendes Adriana Leandra de Assis Christian Dias Cabacinha Jonathan James Stocks Liniker Fernandes da Silva Helio Garcia Leite Agrociencias Forest management Operational research Artificial intelligence In 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. 2018 artículo científico 0104-7760 https://www.redalyc.org/articulo.oa?id=74460167012 https://www.redalyc.org/journal/744/74460167012/ https://www.redalyc.org/journal/744/74460167012/html/ https://www.redalyc.org/journal/744/74460167012/74460167012.epub https://www.redalyc.org/journal/744/74460167012/movil 10.1590/01047760201824032538 en http://www.redalyc.org/revista.oa?id=744 CERNE application/pdf Universidade Federal de Lavras CERNE (Brasil) Num.3 Vol.24
format Artículo científico
id redalyc_74460167012
language en
publishDate 2018
publisher Universidade Federal de Lavras
spellingShingle TUNING OF THE METAHEURISTIC VARIABLE NEIGHBORHOOD SEARCH FOR A FOREST PLANNING PROBLEM
Carlos Alberto Araújo Júnior
Agrociencias
Forest management
Operational research
Artificial intelligence
TUNING OF THE METAHEURISTIC VARIABLE NEIGHBORHOOD SEARCH FOR A FOREST PLANNING PROBLEM Carlos Alberto Araújo Júnior João Batista Mendes Adriana Leandra de Assis Christian Dias Cabacinha Jonathan James Stocks Liniker Fernandes da Silva Helio Garcia Leite Agrociencias Forest management Operational research Artificial intelligence In 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. 2018 artículo científico 0104-7760 https://www.redalyc.org/articulo.oa?id=74460167012 https://www.redalyc.org/journal/744/74460167012/ https://www.redalyc.org/journal/744/74460167012/html/ https://www.redalyc.org/journal/744/74460167012/74460167012.epub https://www.redalyc.org/journal/744/74460167012/movil 10.1590/01047760201824032538 en http://www.redalyc.org/revista.oa?id=744 CERNE application/pdf Universidade Federal de Lavras CERNE (Brasil) Num.3 Vol.24
title TUNING OF THE METAHEURISTIC VARIABLE NEIGHBORHOOD SEARCH FOR A FOREST PLANNING PROBLEM
topic Agrociencias
Forest management
Operational research
Artificial intelligence
url https://www.redalyc.org/articulo.oa?id=74460167012
https://www.redalyc.org/journal/744/74460167012/
https://www.redalyc.org/journal/744/74460167012/html/
https://www.redalyc.org/journal/744/74460167012/74460167012.epub
https://www.redalyc.org/journal/744/74460167012/movil