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.
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© 2014 Springer Japan
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Kodama, K., Nishino, N., Takenaka, T., Koshiba, H. (2014). Modeling Shop Mix Problems as Pareto Optimization Considering Consumer Preference. In: Mochimaru, M., Ueda, K., Takenaka, T. (eds) Serviceology for Services. ICServ 2013. Springer, Tokyo. https://doi.org/10.1007/978-4-431-54816-4_6
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DOI: https://doi.org/10.1007/978-4-431-54816-4_6
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Publisher Name: Springer, Tokyo
Print ISBN: 978-4-431-54815-7
Online ISBN: 978-4-431-54816-4
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