Using simulated annealing and spatial goal programming for solving a multi site land use allocation problem

Jeroen C J H Aerts; Marjan Van Herwijnen; Theodor J. Stewart

Using simulated annealing and spatial goal programming for solving a multi site land use allocation problem

Jeroen C J H Aerts, Marjan Van Herwijnen, Theodor J. Stewart

MSM Decision Sciences

Research output: Chapter in Book/Conference proceeding › Chapter

Abstract

Many resource allocation issues, such as land use- or irrigation planning, require input from extensive spatial databases and involve complex decision-making problems. Recent developments in this field focus on the design of allocation plans that utilize mathematical optimization techniques. These techniques, often referred to as multi criteria decision-making (MCDM) techniques, run into numerical problems when faced with the high dimensionality encountered in spatial applications. In this paper, it is demonstrated how both Simulated annealing, a heuristic algorithm, and Goal Programming techniques can be used to solve high-dimensional optimization problems for multi-site land use allocation (MLUA) problems. The optimization models both minimize development costs and maximize spatial compactness of the allocated land use. The method is applied to a case study in The Netherlands. © Springer-Verlag Berlin Heidelberg 2003.

Original language	English
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)\|Lect. Notes Comput. Sci.
Publisher	Springer Nature
Pages	448-463
Number of pages	15
Volume	2632
Publication status	Published - 2003

Cite this

Aerts, J. C. J. H., Van Herwijnen, M., & Stewart, T. J. (2003). Using simulated annealing and spatial goal programming for solving a multi site land use allocation problem. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci. (Vol. 2632, pp. 448-463). Springer Nature.

Aerts, Jeroen C J H ; Van Herwijnen, Marjan ; Stewart, Theodor J. / Using simulated annealing and spatial goal programming for solving a multi site land use allocation problem. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci.. Vol. 2632 Springer Nature, 2003. pp. 448-463

@inbook{8ccf847564d94ac5a856f33c803e12b2,

title = "Using simulated annealing and spatial goal programming for solving a multi site land use allocation problem",

abstract = "Many resource allocation issues, such as land use- or irrigation planning, require input from extensive spatial databases and involve complex decision-making problems. Recent developments in this field focus on the design of allocation plans that utilize mathematical optimization techniques. These techniques, often referred to as multi criteria decision-making (MCDM) techniques, run into numerical problems when faced with the high dimensionality encountered in spatial applications. In this paper, it is demonstrated how both Simulated annealing, a heuristic algorithm, and Goal Programming techniques can be used to solve high-dimensional optimization problems for multi-site land use allocation (MLUA) problems. The optimization models both minimize development costs and maximize spatial compactness of the allocated land use. The method is applied to a case study in The Netherlands. {\textcopyright} Springer-Verlag Berlin Heidelberg 2003.",

author = "Aerts, {Jeroen C J H} and {Van Herwijnen}, Marjan and Stewart, {Theodor J.}",

year = "2003",

language = "English",

volume = "2632",

pages = "448--463",

booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci.",

publisher = "Springer Nature",

address = "United States",

}

Using simulated annealing and spatial goal programming for solving a multi site land use allocation problem. / Aerts, Jeroen C J H; Van Herwijnen, Marjan; Stewart, Theodor J.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci.. Vol. 2632 Springer Nature, 2003. p. 448-463.

Research output: Chapter in Book/Conference proceeding › Chapter

TY - CHAP

T1 - Using simulated annealing and spatial goal programming for solving a multi site land use allocation problem

AU - Aerts, Jeroen C J H

AU - Van Herwijnen, Marjan

AU - Stewart, Theodor J.

PY - 2003

Y1 - 2003

N2 - Many resource allocation issues, such as land use- or irrigation planning, require input from extensive spatial databases and involve complex decision-making problems. Recent developments in this field focus on the design of allocation plans that utilize mathematical optimization techniques. These techniques, often referred to as multi criteria decision-making (MCDM) techniques, run into numerical problems when faced with the high dimensionality encountered in spatial applications. In this paper, it is demonstrated how both Simulated annealing, a heuristic algorithm, and Goal Programming techniques can be used to solve high-dimensional optimization problems for multi-site land use allocation (MLUA) problems. The optimization models both minimize development costs and maximize spatial compactness of the allocated land use. The method is applied to a case study in The Netherlands. © Springer-Verlag Berlin Heidelberg 2003.

AB - Many resource allocation issues, such as land use- or irrigation planning, require input from extensive spatial databases and involve complex decision-making problems. Recent developments in this field focus on the design of allocation plans that utilize mathematical optimization techniques. These techniques, often referred to as multi criteria decision-making (MCDM) techniques, run into numerical problems when faced with the high dimensionality encountered in spatial applications. In this paper, it is demonstrated how both Simulated annealing, a heuristic algorithm, and Goal Programming techniques can be used to solve high-dimensional optimization problems for multi-site land use allocation (MLUA) problems. The optimization models both minimize development costs and maximize spatial compactness of the allocated land use. The method is applied to a case study in The Netherlands. © Springer-Verlag Berlin Heidelberg 2003.

M3 - Chapter

VL - 2632

SP - 448

EP - 463

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci.

PB - Springer Nature

ER -

Using simulated annealing and spatial goal programming for solving a multi site land use allocation problem

Abstract

Fingerprint

Cite this