Comparing exact and heuristic methods for site location based on multiple attributes: An afforestation application

Pablo Vanegas; Dirk Cattrysse; Jos Van Orshoven

doi:10.1007/978-3-540-69839-5_29

Comparing exact and heuristic methods for site location based on multiple attributes: An afforestation application

Pablo Vanegas, Dirk Cattrysse, Jos Van Orshoven

KU Leuven

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

11 Citas (Scopus)

Resumen

This paper presents a mathematical formulation and a heuristic solution method in order to locate optimal sites for afforestation of agricultural land. These sites must maximize levels of environmental performance, and must fulfill shape and size requirements. Since the criteria involved in the problem are represented by means of raster structures, the sites are composed by a given number of cells. The ultimate objective of this work is the development of a high performance heuristic able to find near to optimal afforestation sites. For validating the heuristic approach, a comparison with the mathematical method is carried out in limited sized areas within The Netherlands, Denmark, and Flanders. The comparison reveals that the heuristic is considerably faster than the mathematical method, and that the objective values obtained with the two approaches are significantly similar.

Idioma original	Inglés
Título de la publicación alojada	Computational Science and Its Applications - ICCSA 2008 - International Conference, Proceedings
Páginas	389-404
Número de páginas	16
Edición	PART 1
DOI	https://doi.org/10.1007/978-3-540-69839-5_29
Estado	Publicada - 2008
Publicado de forma externa	Sí
Evento	International Conference on Computational Science and Its Applications, ICCSA 2008 - Perugia, Italia Duración: 30 jun. 2008 → 3 jul. 2008

Serie de la publicación

Nombre	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Número	PART 1
Volumen	5072 LNCS
ISSN (versión impresa)	0302-9743
ISSN (versión digital)	1611-3349

Conferencia

Conferencia	International Conference on Computational Science and Its Applications, ICCSA 2008
País/Territorio	Italia
Ciudad	Perugia
Período	30/06/08 → 3/07/08

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

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10.1007/978-3-540-69839-5_29

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Vanegas, P., Cattrysse, D., & Van Orshoven, J. (2008). Comparing exact and heuristic methods for site location based on multiple attributes: An afforestation application. En Computational Science and Its Applications - ICCSA 2008 - International Conference, Proceedings (PART 1 ed., pp. 389-404). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5072 LNCS, N.º PART 1). https://doi.org/10.1007/978-3-540-69839-5_29

Vanegas, Pablo ; Cattrysse, Dirk ; Van Orshoven, Jos. / Comparing exact and heuristic methods for site location based on multiple attributes : An afforestation application. Computational Science and Its Applications - ICCSA 2008 - International Conference, Proceedings. PART 1. ed. 2008. pp. 389-404 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).

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title = "Comparing exact and heuristic methods for site location based on multiple attributes: An afforestation application",

abstract = "This paper presents a mathematical formulation and a heuristic solution method in order to locate optimal sites for afforestation of agricultural land. These sites must maximize levels of environmental performance, and must fulfill shape and size requirements. Since the criteria involved in the problem are represented by means of raster structures, the sites are composed by a given number of cells. The ultimate objective of this work is the development of a high performance heuristic able to find near to optimal afforestation sites. For validating the heuristic approach, a comparison with the mathematical method is carried out in limited sized areas within The Netherlands, Denmark, and Flanders. The comparison reveals that the heuristic is considerably faster than the mathematical method, and that the objective values obtained with the two approaches are significantly similar.",

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Vanegas, P, Cattrysse, D & Van Orshoven, J 2008, Comparing exact and heuristic methods for site location based on multiple attributes: An afforestation application. En Computational Science and Its Applications - ICCSA 2008 - International Conference, Proceedings. PART 1 ed., Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), n.º PART 1, vol. 5072 LNCS, pp. 389-404, International Conference on Computational Science and Its Applications, ICCSA 2008, Perugia, Italia, 30/06/08. https://doi.org/10.1007/978-3-540-69839-5_29

Comparing exact and heuristic methods for site location based on multiple attributes: An afforestation application. / Vanegas, Pablo; Cattrysse, Dirk; Van Orshoven, Jos.
Computational Science and Its Applications - ICCSA 2008 - International Conference, Proceedings. PART 1. ed. 2008. p. 389-404 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5072 LNCS, N.º PART 1).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

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AU - Cattrysse, Dirk

AU - Van Orshoven, Jos

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N2 - This paper presents a mathematical formulation and a heuristic solution method in order to locate optimal sites for afforestation of agricultural land. These sites must maximize levels of environmental performance, and must fulfill shape and size requirements. Since the criteria involved in the problem are represented by means of raster structures, the sites are composed by a given number of cells. The ultimate objective of this work is the development of a high performance heuristic able to find near to optimal afforestation sites. For validating the heuristic approach, a comparison with the mathematical method is carried out in limited sized areas within The Netherlands, Denmark, and Flanders. The comparison reveals that the heuristic is considerably faster than the mathematical method, and that the objective values obtained with the two approaches are significantly similar.

AB - This paper presents a mathematical formulation and a heuristic solution method in order to locate optimal sites for afforestation of agricultural land. These sites must maximize levels of environmental performance, and must fulfill shape and size requirements. Since the criteria involved in the problem are represented by means of raster structures, the sites are composed by a given number of cells. The ultimate objective of this work is the development of a high performance heuristic able to find near to optimal afforestation sites. For validating the heuristic approach, a comparison with the mathematical method is carried out in limited sized areas within The Netherlands, Denmark, and Flanders. The comparison reveals that the heuristic is considerably faster than the mathematical method, and that the objective values obtained with the two approaches are significantly similar.

KW - Exact methods

KW - Heuristic

KW - Site location

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SN - 9783540698388

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Vanegas P, Cattrysse D, Van Orshoven J. Comparing exact and heuristic methods for site location based on multiple attributes: An afforestation application. En Computational Science and Its Applications - ICCSA 2008 - International Conference, Proceedings. PART 1 ed. 2008. p. 389-404. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). doi: 10.1007/978-3-540-69839-5_29

Comparing exact and heuristic methods for site location based on multiple attributes: An afforestation application

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