Optimal subdivision of land in agrarian reform projects: an analysis using genetic algorithms

The objective of this manuscript is to develop a new procedure to achieve optimal land subdivision using genetic algorithms (GA). The genetic algorithm was tested in the rural settlement of Veredas, located in Minas Gerais, Brazil. This implementation was based on the land aptitude and its productiv...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Ferreira Neto,José Ambrósio, Carneiro dos Santos Junior,Edgard, Fra Paleo,Urbano, Miranda Barros,David, César de Oliveira Moreira,Mayron
Lenguaje:	English
Publicado:	Pontificia Universidad Católica de Chile. Facultad de Agronomía e Ingeniería Forestal 2011
Materias:	Agrarian reform genetic algorithm rural settlement spatial planning
Acceso en línea:	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-16202011000200001
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:scielo:S0718-16202011000200001
record_format	dspace
spelling	oai:scielo:S0718-162020110002000012011-09-01Optimal subdivision of land in agrarian reform projects: an analysis using genetic algorithmsFerreira Neto,José AmbrósioCarneiro dos Santos Junior,EdgardFra Paleo,UrbanoMiranda Barros,DavidCésar de Oliveira Moreira,Mayron Agrarian reform genetic algorithm rural settlement spatial planning The objective of this manuscript is to develop a new procedure to achieve optimal land subdivision using genetic algorithms (GA). The genetic algorithm was tested in the rural settlement of Veredas, located in Minas Gerais, Brazil. This implementation was based on the land aptitude and its productivity index. The sequence of tests in the study was carried out in two areas with eight different agricultural aptitude classes, including one area of 391.88 ha subdivided into 12 lots and another of 404.1763 ha subdivided into 14 lots. The effectiveness of the method was measured using the shunting line standard value of a parceled area lot's productivity index. To evaluate each parameter, a sequence of 15 calculations was performed to record the best individual fitness average (MMI) found for each parameter variation. The best parameter combination found in testing and used to generate the new parceling with the GA was the following: 320 as the generation number, a population of 40 individuals, 0.8 mutation tax, and a 0.3 renewal tax. The solution generated rather homogeneous lots in terms of productive capacity.info:eu-repo/semantics/openAccessPontificia Universidad Católica de Chile. Facultad de Agronomía e Ingeniería ForestalCiencia e investigación agraria v.38 n.2 20112011-08-01text/htmlhttp://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-16202011000200001en10.4067/S0718-16202011000200001
institution	Scielo Chile
collection	Scielo Chile
language	English
topic	Agrarian reform genetic algorithm rural settlement spatial planning
spellingShingle	Agrarian reform genetic algorithm rural settlement spatial planning Ferreira Neto,José Ambrósio Carneiro dos Santos Junior,Edgard Fra Paleo,Urbano Miranda Barros,David César de Oliveira Moreira,Mayron Optimal subdivision of land in agrarian reform projects: an analysis using genetic algorithms
description	The objective of this manuscript is to develop a new procedure to achieve optimal land subdivision using genetic algorithms (GA). The genetic algorithm was tested in the rural settlement of Veredas, located in Minas Gerais, Brazil. This implementation was based on the land aptitude and its productivity index. The sequence of tests in the study was carried out in two areas with eight different agricultural aptitude classes, including one area of 391.88 ha subdivided into 12 lots and another of 404.1763 ha subdivided into 14 lots. The effectiveness of the method was measured using the shunting line standard value of a parceled area lot's productivity index. To evaluate each parameter, a sequence of 15 calculations was performed to record the best individual fitness average (MMI) found for each parameter variation. The best parameter combination found in testing and used to generate the new parceling with the GA was the following: 320 as the generation number, a population of 40 individuals, 0.8 mutation tax, and a 0.3 renewal tax. The solution generated rather homogeneous lots in terms of productive capacity.
author	Ferreira Neto,José Ambrósio Carneiro dos Santos Junior,Edgard Fra Paleo,Urbano Miranda Barros,David César de Oliveira Moreira,Mayron
author_facet	Ferreira Neto,José Ambrósio Carneiro dos Santos Junior,Edgard Fra Paleo,Urbano Miranda Barros,David César de Oliveira Moreira,Mayron
author_sort	Ferreira Neto,José Ambrósio
title	Optimal subdivision of land in agrarian reform projects: an analysis using genetic algorithms
title_short	Optimal subdivision of land in agrarian reform projects: an analysis using genetic algorithms
title_full	Optimal subdivision of land in agrarian reform projects: an analysis using genetic algorithms
title_fullStr	Optimal subdivision of land in agrarian reform projects: an analysis using genetic algorithms
title_full_unstemmed	Optimal subdivision of land in agrarian reform projects: an analysis using genetic algorithms
title_sort	optimal subdivision of land in agrarian reform projects: an analysis using genetic algorithms
publisher	Pontificia Universidad Católica de Chile. Facultad de Agronomía e Ingeniería Forestal
publishDate	2011
url	http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0718-16202011000200001
work_keys_str_mv	AT ferreiranetojoseambrosio optimalsubdivisionoflandinagrarianreformprojectsananalysisusinggeneticalgorithms AT carneirodossantosjunioredgard optimalsubdivisionoflandinagrarianreformprojectsananalysisusinggeneticalgorithms AT frapaleourbano optimalsubdivisionoflandinagrarianreformprojectsananalysisusinggeneticalgorithms AT mirandabarrosdavid optimalsubdivisionoflandinagrarianreformprojectsananalysisusinggeneticalgorithms AT cesardeoliveiramoreiramayron optimalsubdivisionoflandinagrarianreformprojectsananalysisusinggeneticalgorithms
_version_	1714202130711052288

Optimal subdivision of land in agrarian reform projects: an analysis using genetic algorithms

Ejemplares similares