Spatially informed p-dispersion problem and efficient solution approach
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Keywords: spatial optimization, operations research, p-dispersion
Abstract Type: Paper Abstract
Authors:
Changwha Oh, University of Tennessee, Knoxville
Hyun Kim, University of Tennessee, Knoxville
Yongwan Chun, University of Texas Dallas
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Abstract
The p-dispersion problem is a spatial optimization problem that maximizes the minimum separation distance among all assigned nodes. The p-dispersion entails an innate spatial autocorrelation structure and, thus, distance-based spatially informed property (DSIP) driven from the behavior of the optimal solutions prescribes a strategy to improve its model performance for solving large-size instances effectively. This research aims to explore spatial characteristics in the optimal solutions of the p-dispersion problem via simulations by spatial point patterns. We utilize Ripley’s k-function to discover the spatial characteristics to identify essential decision variables because the optimal solutions of the p-dispersion problem are considerably associated with the distances among points. The results of the experiments uncovered the relationship between the DSIP and the behavior of the optimal solutions, which indicates that the DSIP underlying the p-dispersion problem rationalizes the construction of an efficient exact, or strong heuristic approach to enhance the solvability of the problem.
Spatially informed p-dispersion problem and efficient solution approach
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Paper Abstract
