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Submodularity Property for Facility Locations of Dynamic Flow Networks

Authors Peerawit Suriya, Vorapong Suppakitpaisarn , Supanut Chaidee , Phapaengmueng Sukkasem

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Author Details

Peerawit Suriya
  • Department of Mathematics, Faculty of Science, Chiang Mai University, Thailand
Vorapong Suppakitpaisarn
  • Graduate School of Information Science and Technology, The University of Tokyo, Japan
Supanut Chaidee
  • Department of Mathematics, Faculty of Science, Chiang Mai University, Thailand
Phapaengmueng Sukkasem
  • Department of Mathematics, Faculty of Science, Chiang Mai University, Thailand

Funding

This research is partially supported by Chiang Mai University as a part of the One Faculty One MoU Project.
  • Suriya, Peerawit: Supported by the Development and Promotion of Science and Technology Talents Project (DPST) under The Institute for the Promotion of Teaching Science and Technology (IPST), Ministry of Education, Thailand.
  • Suppakitpaisarn, Vorapong: Supported by JSPS Grant-in-Aid for Transformative Research Areas A grant number JP21H05845, and also by JST SICORP Grant Number JPMJSC2208, Japan.

Cite AsGet BibTex

Peerawit Suriya, Vorapong Suppakitpaisarn, Supanut Chaidee, and Phapaengmueng Sukkasem. Submodularity Property for Facility Locations of Dynamic Flow Networks. In 23rd Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2023). Open Access Series in Informatics (OASIcs), Volume 115, pp. 10:1-10:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)
https://doi.org/10.4230/OASIcs.ATMOS.2023.10

Abstract

This paper considers facility location problems within dynamic flow networks, shifting the focus from minimizing evacuation time to handling situations with a constrained evacuation timeframe. Our study sets two main goals: 1) Determining a fixed-size set of locations that can maximize the number of evacuees, and 2) Identifying the smallest set of locations capable of accommodating all evacuees within the time constraint. We introduce flow_t(S) to represent the number of evacuees for given locations S within a fixed time limit t. We prove that flow_t functions is a monotone submodular function, which allows us to apply an approximation algorithm specifically designed for maximizing such functions with size restrictions. For the second objective, we implement an approximation algorithm tailored to solving the submodular cover problem. We conduct experiments on the real datasets of Chiang Mai, and demonstrate that the approximation algorithms give solutions which are close to optimal for all of the experiments we have conducted.

Subject Classification

ACM Subject Classification
  • Theory of computation → Network flows
  • Theory of computation → Dynamic graph algorithms
  • Theory of computation → Routing and network design problems
Keywords
  • Approximation Algorithms
  • Dynamic Networks
  • Facility Location
  • Submodular Function Optimization

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