Multiple Subregion Allocation Models

Benabdallah, Salah; Wright, Jeff R.

doi:10.1061/(asce)0733-9488(1992)118:1(24)

Cited by 34 publications

(20 citation statements)

References 10 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%

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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%

“…Most subregion districting models have been constructed for developing voting districts or sales territories. [7][8][9][10][11][12] Among these studies,…”

Section: Introductionmentioning

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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“…Land-use allocation can be defined as: making constitute of different land use type according to land use character and systemic principle so that to get optimal economic and ecological goals, which can achieve the best land use effectiveness and keep a balance ecosystem status (Benabdallah and Wright 1992). Land-use allocation is the fundamental way to resolve regional land use issues (Sadeghi et al 2009).…”

Section: Introductionmentioning

confidence: 99%

An interval fuzzy land-use allocation model (IFLAM) for Beijing in association with environmental and ecological consideration under uncertainty

et al. 2014

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In this study, an interval fuzzy land-use allocation method (IFLAM) is developed for the planning of urban land-use allocation system. The developed IFLAM method is based on interval parameter programming technique and fuzzy flexible programming, which could handle uncertainties expressed as interval values and fuzzy sets in the model's left-and righthand sides and objective function. A management problem for allocating land resources of Beijing, the capital of China, is studied to illustrate applicability of the proposed IFLAM approach. Results show that the optimized λ values (which means the satisfaction degree of all model constraints) are in the range of [0.67, 0.89], and the corresponding system benefit is between $ [534.03, 698.75] × 10 12 and $ [961.37, 1028.33] × 10 12 while the optimized urban land in the first studying period will be [71905, 77894] ha in the Function Central Zone, [35219, 39711] ha in the Function Extended Zone, [22012, 30547] ha in the New Urban Zone and [17609, 22910] ha in the Eco-Conservation Zone. Results indicate that reasonable solutions have been generated under various environmental, ecological and social conditions. They can help decision makers to identify desired alternatives for making the utmost of land resources of Beijing and for providing services for urban land management 123 M. Zhou et al.decisions; moreover, they are helpful for land managers to gain insight into the tradeoff between economic objective and eco-environment violation risk.

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“…Spatial units involved in spatial allocation may be socioeconomic ones such as counties, Zip-code areas, census tracts, and land parcels [17], or results of systematic sampling such as pixels and grid cells [45]. There are different terms for clusters to which spatial units are allocated, such as Bzones'' [45], Bregions'' [6], Bdistricts'' [28], Bterritories'' [27], and Bturfs'' [38] depending on context. They are herein referred to as Bobjects'' for generality.…”

Section: Introductionmentioning

confidence: 99%

“…Spatial allocation encompasses a wide variety of applications ranging from school districting [4], [19], [53] and political districting [21], [28], [29], [36], to market analysis [18], [27], [34], [38], [39], [47], [54], to land use planning [13], [14], [46] and site selection [5], [6], [12], [22], [52]. While required criteria vary from one application to another, they tend to relate to spatial properties such as population Bsize,'' compact Bshape,'' and distant Bspatial relation.''…”

Section: Introductionmentioning

confidence: 99%

Classification of Spatial Properties for Spatial Allocation Modeling

Shirabe

2005

Geoinformatica

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Given a set of spatial units, such as land parcels and grid cells, how to allocate subsets of it to activities of interest while satisfying certain criteria? Such a decision process is here called spatial allocation. Though many problems of spatial allocation share this generic construct, each may have a quite unique set of criteria and interpret even the same criteria in its own way. Such diversity makes it difficult to model spatial allocation problems in unambiguous terms that are amenable to algorithmic solution. This paper proposes a classification scheme for spatial properties that helps to address a variety of spatial properties in establishing spatial allocation criteria. The implication of the paper is that a number of spatial properties and spatial allocation criteria can be decomposed into a few kinds of primitive spatial properties and their relations.

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Multiple Subregion Allocation Models

Cited by 34 publications

References 10 publications

Subregion Districting Analysis for Municipal Solid Waste Collection Privatization

Subregion Districting Analysis for Municipal Solid Waste Collection Privatization

An interval fuzzy land-use allocation model (IFLAM) for Beijing in association with environmental and ecological consideration under uncertainty

Classification of Spatial Properties for Spatial Allocation Modeling

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