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Multiple Resource Network Voronoi Diagram

Authors Ahmad Qutbuddin , KwangSoo Yang

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Author Details

Ahmad Qutbuddin
  • Department of Computer and Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL, USA
KwangSoo Yang
  • Department of Computer and Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL, USA

Funding

This work is supported by the National Science Foundation CAREER under Grant No. 1844565.

Acknowledgements

We would like to thank the US National Science Foundation under Grant No. 1844565. We are particularly thankful to GIScience reviewers for their helpful comments.

Cite As Get BibTex

Ahmad Qutbuddin and KwangSoo Yang. Multiple Resource Network Voronoi Diagram. In 11th International Conference on Geographic Information Science (GIScience 2021) - Part I. Leibniz International Proceedings in Informatics (LIPIcs), Volume 177, pp. 11:1-11:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020) https://doi.org/10.4230/LIPIcs.GIScience.2021.I.11

Abstract

Given a spatial network and a set of service center nodes from k different resource types, a Multiple Resource-Network Voronoi Diagram (MRNVD) partitions the spatial network into a set of Service Areas that can minimize the total cycle distances of graph-nodes to allotted k service center nodes with different resource types. The MRNVD problem is important for critical societal applications such as assigning essential survival supplies (e.g., food, water, gas, and medical assistance) to residents impacted by man-made or natural disasters. The MRNVD problem is NP-hard; it is computationally challenging due to the large size of the transportation network. Previous work is limited to a single or two different types of service centers, but cannot be generalized to deal with k different resource types. We propose a novel approach for MRNVD that can efficiently identify the best routes to obtain the k different resources. Experiments and a case study using real-world datasets demonstrate that the proposed approach creates MRNVD and significantly reduces the computational cost.

Subject Classification

ACM Subject Classification
  • Information systems → Geographic information systems
Keywords
  • Network Voronoi Diagram
  • Resource Allocation
  • Route Optimization

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References

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