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Business and Consumer Analytics: New Ideas pp 637–660Cite as

A Memetic Algorithm for Competitive Facility Location Problems

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Abstract

We study a memetic algorithm to solve diverse variants of competitive facility location problems. Two non-cooperating companies enter a market sequentially and compete for market share. The first decision maker, the leader, aims to choose a set of locations which maximize his market share knowing that a follower will enter the same market, lowering the leader’s market share. For this bi-level combinatorial optimization problem several customer behaviour scenarios and demand models are studied. A memetic algorithm is applied to find a good set of locations for the leader and the solution evaluation consisting of finding near optimal locations for the follower is performed by greedy algorithms and the use of mixed integer linear programming models. We conclude this chapter with a case study for two hypermarket chains who both want to open stores in Vienna using real world demographic data. In this study we consider six different customer behaviour scenarios and present numerical and graphical results which show the effectiveness of the presented approach.

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Notes

  1. 1.

    https://www.data.gv.at/auftritte/?organisation=stadt-wien.

  2. 2.

    http://www.wu.ac.at/inst/iir/datarchive/dist_zbez.html.

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Acknowledgement

This work is supported by the Austrian Science Fund (FWF) under grant P24660-N23.

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Authors and Affiliations

  1. Institute of Computer Graphics and Algorithms, TU Wien, Vienna, Austria

    Benjamin Biesinger & Günther R. Raidl

  2. AIT Austrian Institute of Technology, Mobility Department - Dynamic Transportation Systems, Vienna, Austria

    Bin Hu

Authors
  1. Benjamin Biesinger
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  2. Bin Hu
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  3. Günther R. Raidl
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Correspondence to Benjamin Biesinger .

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Editors and Affiliations

  1. School of Electrical Engineering and Computing, The University of Newcastle, Callaghan, NSW, Australia

    Pablo Moscato

  2. School of Electrical Engineering and Computing, The University of Newcastle, Callaghan, NSW, Australia

    Natalie Jane de Vries

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Biesinger, B., Hu, B., Raidl, G.R. (2019). A Memetic Algorithm for Competitive Facility Location Problems. In: Moscato, P., de Vries, N. (eds) Business and Consumer Analytics: New Ideas. Springer, Cham. https://doi.org/10.1007/978-3-030-06222-4_15

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  • DOI: https://doi.org/10.1007/978-3-030-06222-4_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-06221-7

  • Online ISBN: 978-3-030-06222-4

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