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Modeling Shop Mix Problems as Pareto Optimization Considering Consumer Preference

  • Keita Kodama
  • Nariaki Nishino
  • Takeshi Takenaka
  • Hitoshi Koshiba
Chapter

Abstract

This study models a shop mix problem in a large-scale shopping center, aiming at realizing Pareto optimization of consumer preference. Our study defines a consumer preference order to respective shops as a two-level hierarchy obtained by computation from the “repeat rate” in reference data from actual POS. The combinatorial problem that preference order should be Pareto-improved is modeled and solved with a genetic algorithm. Results show that positively preferred shops do not coincide with the shops with a high average repeat rate. Results show that our method using a repeat rate is a good indicator for tenant replacement planning.

Keywords

Genetic algorithm Operation research Optimization Service engineering 

References

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    Takenaka T et al (2013) Modeling customer behaviors in a shopping mall; tenant variety and customer types. In: Proceedings of 1st international conference on serviceology (ICServ2013) (to appear)Google Scholar
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    Holland J (1975) Adaptation in Natural and Artificial Systems. The University of Michigan Press, Ann ArborGoogle Scholar

Copyright information

© Springer Japan 2014

Authors and Affiliations

  • Keita Kodama
    • 1
  • Nariaki Nishino
    • 1
  • Takeshi Takenaka
    • 2
  • Hitoshi Koshiba
    • 2
  1. 1.School of EngineeringThe University of TokyoTokyoJapan
  2. 2.National Institute of Advanced Industrial Science and TechnologyTokyoJapan

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