A multiobjective integer programming model for the land acquisition problem

Wright, Jeff R.; ReVelle, Charles; Cohon, Jared L.

doi:10.1016/0166-0462(83)90004-2

Cited by 122 publications

(93 citation statements)

References 6 publications

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“…Several enhancements, 8,10 including heuristic approaches, for solving the same model were also developed. Benedallah et al 9 proposed an MIP model, a modified version of the model developed by Wright et al 15 for siting a single subregion to solve a multiple subregion allocation problem. In our previous work, 13 a MIP model was developed for siting a landfill.…”

Section: Discussionmentioning

confidence: 99%

Subregion Districting Analysis for Municipal Solid Waste Collection Privatization

Lin

Kao

2008

Journal of the Air & Waste Management Association

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Privatization of municipal solid waste (MSW) collection can improve service quality and reduce cost. To reduce the risk of an incapable company serving an entire collection area and to establish a competitive market, a large collection area should be divided into two or more subregions, with each subregion served by a different company. The MSW subregion districting is generally done manually, based on the planner's intuition. Major drawbacks of a manual approach include the creation of a districting plan with poor road network integrity for which it is difficult to design an efficient collection route. The other drawbacks are difficulty in finding the optimal districting plan and the lack of a way to consistently measure the differences among subregions to avoid unfair competition. To determine an MSW collection subregion districting plan, this study presents a mixed-integer optimization model that incorporates factors such as compactness, road network integrity, collection cost, and regional proximity. Two cases are presented to demonstrate the applicability of the proposed model. In both cases, districting plans with good road network integrity and regional proximity have been generated successfully.

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Section: Discussionmentioning

confidence: 99%

Subregion Districting Analysis for Municipal Solid Waste Collection Privatization

Lin

Kao

2008

Journal of the Air & Waste Management Association

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“…In this model, we replace the previous definition of compactness by another measure, which is a concept proposed by Williams andReVelle (1996,1998) and Wright, ReVelle, and Cohon (1983). They describe a problem where one selects parcels of land for inclusion within a protected reserve.…”

Section: Model 3: a Linear Integer Program Using Bufer Cellsmentioning

confidence: 99%

“…Most of the existing IP models encourage compactness by pursuing a low perimeter-to-area ratio of an allocated site of land use (e.g., Wright, ReVelle, and Cohon 1983;Gilbert, Holmes, and Rosenthal 1985;Benabdallah andWright 1991, 1992;Minor and Jacobs 1994;Cova and Church 2000). Studies as Williams (1995) and Cova (1999) summarize available IP models and techniques for solving single site land use allocation problems.…”

Section: Adding a Compactness Objective To The Mlua Problemmentioning

confidence: 99%

Using Linear Integer Programming for Multi‐Site Land‐Use Allocation

Aerts¹,

Eisinger

Heuvelink³

et al. 2003

Geographical Analysis

176

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“…The landscape is to be partitioned into two regions by assigning each cell to one region or the other. One of the regions contains those cells selected for acquisition (for a particular land use, for example, green space) and the other region contains the remaining (unselected) cells.The land acquisition problem was introduced as an optimization problem by Wright, ReVelle, and Cohon (1983) who formulated a zero-one programming model with three objectives: minimize the total cost of selected cells; maximize total area; and maximize compactness. The last objective was achieved by minimizing the total external border length of selected cells.…”

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confidence: 99%

A Zero-One Programming Model for Contiguous Land Acquisition

Williams¹

2002

Geographical Analysis

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The land acquisition problem is a spatial partitioning problem that involves selecting multiple parcels to be acquired for a particular land use. Three selection criteria are considered: total cost, total area, and spatial contiguity. Achieving contiguity or connectivity has been problematic in previous exact methods for land acquisition. Here we present a new zero-one programming model that enforces necessa y and sufficient conditions for achieving contiguity in discrete cell landscapes, independent of other spatial attributes such as compactness. Computational experience with several demonstration problems is reported, and results and extensions are discussed.Spatial partitioning problems, in which the landscape is divided into distinct regions or zones, are ubiquitous in geography and planning. They have appeared as "regionalization" problems (Nutenko 1970), "region building" problems (Cliff and Haggett 1970; Keane 1975), "districting" problems (Horn 1995; Williams 1995), "clustering" problems (Rosing and ReVelle 1986), "land acquisition/ allocation" problems (Wright, ReVelle, and Cohon 1983; Gilbert et al. 1985; Diamond and Wright 1991; Cova and Church ZOOO), and "reserve design" problems (Williams and ReVelle 1996). In addition, facility siting problems such as the p-median problem (ReVelle and Swain 1970), as well as the delineation of market areas in central place theory (Dacey 1965), also involve partitioning space into a set of distinct regions.In this paper we address a particular type of spatial partitioning problem, the land acquisition problem, which can be described in the following way. We are given a two-dimensional landscape that is represented as a set of n discrete parcels or cells. The landscape is to be partitioned into two regions by assigning each cell to one region or the other. One of the regions contains those cells selected for acquisition (for a particular land use, for example, green space) and the other region contains the remaining (unselected) cells.The land acquisition problem was introduced as an optimization problem by Wright, ReVelle, and Cohon (1983) who formulated a zero-one programming model with three objectives: minimize the total cost of selected cells; maximize total area; and maximize compactness. The last objective was achieved by minimizing the total external border length of selected cells. The authors employed multiobjective linear programming together with a branch-and-bound routine to find all pareto-optimal or Justin C. Williams is associate research professor of geography and environmental engineering at Johns Hopkins University.

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A multiobjective integer programming model for the land acquisition problem

Cited by 122 publications

References 6 publications

Subregion Districting Analysis for Municipal Solid Waste Collection Privatization

Subregion Districting Analysis for Municipal Solid Waste Collection Privatization

Using Linear Integer Programming for Multi‐Site Land‐Use Allocation

A Zero-One Programming Model for Contiguous Land Acquisition

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