Using Voronoi diagrams to solve a hybrid facility location problem with attentive facilities

In this paper, we introduce a novel class of facility location problems, and propose solutions based on Voronoi diagrams. Our solutions locate a set of facilities on a two dimensional space, with respect to a set of dynamic demand. The information about these demand is gathered through modifications of the overall system, into a central decision unit. This influences our objective of minimizing the total loss function. Considering a continuous space and discrete time, facilities are assigned to meet demands in each time cycle. Two distinct approaches are proposed and thoroughly studied, followed by a case study. We call our main algorithm Reactive Agent Dynamic Voronoi Diagram Facility Spread. We also test our solutions empirically through a set of experiments. Considering n and p to be the number of demand points, and the number of facilities in hand, respectively, the time complexity of the algorithm is Oðcðn2 þ pÞlognÞ for a complete run of c cycles.

Publication Details

Journal
Figshare
Published
2025-08-15
DOI
https://doi.org/10.6084/m9.figshare.29921888
Primary Topic
Facility Location and Emergency Management
Type
article
Field-Weighted Citation Impact
0.00
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article

Using Voronoi diagrams to solve a hybrid facility location problem with attentive facilities

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Facility Location and Emergency Management
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Using Voronoi diagrams to solve a hybrid facility location problem with attentive facilities

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Abstract

In this paper, we introduce a novel class of facility location problems, and propose solutions based on Voronoi diagrams. Our solutions locate a set of facilities on a two dimensional space, with respect to a set of dynamic demand. The information about these demand is gathered through modifications of the overall system, into a central decision unit. This influences our objective of minimizing the total loss function. Considering a continuous space and discrete time, facilities are assigned to meet demands in each time cycle. Two distinct approaches are proposed and thoroughly studied, followed by a case study. We call our main algorithm Reactive Agent Dynamic Voronoi Diagram Facility Spread. We also test our solutions empirically through a set of experiments. Considering n and p to be the number of demand points, and the number of facilities in hand, respectively, the time complexity of the algorithm is Oðcðn2 þ pÞlognÞ for a complete run of c cycles.

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Openalex Percentile: Top 47%
Facility Location and Emergency Management
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