Efficient identification of geographic restriction conditions in anti-covering location models using GIS

Spatial separation in located services and activities is often essential. Examples include homeland security, military asset defense, impacts on the environment, franchise outlet location, and promoting public wellbeing. When planning and management is supported by mathematical modeling, a difficulty has been efficient representation of spatial separation conditions. This paper reviews an optimization model, the anti-covering location problem, used to support planning and management problems where spatial separation must be ensured between sited services/activities. An approach is presented for the efficient and effective identification and use of spatial separation conditions called cliques in this model based upon the use of a geographic information system (GIS). Results highlight the significance of the developed methodology in terms of computational requirements, tractability and effectiveness. This research enhances capabilities for addressing important practical planning problems.

[1]  J. Douglas Brodie,et al.  Adjacency constraints in harvest scheduling: an aggregation heuristic , 1990 .

[2]  Francisco Barahona,et al.  Harvest Scheduling Subject to Maximum Area Restrictions: Exploring Exact Approaches , 2005, Oper. Res..

[3]  Glaydston Mattos Ribeiro,et al.  A greedy randomized adaptive search procedure for the point-feature cartographic label placement , 2008, Comput. Geosci..

[4]  Manfred W. Padberg,et al.  On the facial structure of set packing polyhedra , 1973, Math. Program..

[5]  G. Nemhauser,et al.  A Strong Cutting Plane/Branch-and-Bound Algorithm for Node Packing , 1992 .

[6]  Richard L. Church,et al.  Business Site Selection, Location Analysis and GIS , 2008 .

[7]  Alan T. Murray,et al.  Constructing And Selecting Adjacency Constraints , 1996 .

[8]  Alan T. Murray.  Spatial restrictions in harvest scheduling , 1999 .

[9]  Alan T. Murray,et al.  Estimating carrying capacity for sandhill cranes using habitat suitability and spatial optimization models , 2008 .

[10]  J. G. Jones,et al.  Formulating adjacency constraints in linear optimization models for scheduling projects in tactical planning , 1991 .

[11]  C. Revelle,et al.  Integer-friendly formulations for the r-separation problem , 1996 .

[12]  I. Moon,et al.  An Analysis of Network Location Problems with Distance Constraints , 1984 .

[13]  Richard L. Church,et al.  Facets for node packing , 1997 .

[14]  Sohail S. Chaudhry,et al.  A genetic algorithm approach to solving the anti‐covering location problem , 2006, Expert Syst. J. Knowl. Eng..

[15]  Alan T. Murray,et al.  Business Site Selection, Location Analysis and GIS: Church/BUSINESS , 2008 .

[16]  Leslie E. Trotter,et al.  Vertex packings: Structural properties and algorithms , 1975, Math. Program..

[17]  Alan T. Murray,et al.  Sex Offender Residency and Spatial Equity , 2008 .

[18]  Sheng-Roan Kai,et al.  Design and Implementation of an Interactive Optimization System for Telephone Network Planning , 1992, Oper. Res..

[19]  Alan T. Murray,et al.  Measuring the efficacy of adjacency constraint structure in forest planning models , 1995 .