Abstract
The location problem of unmanned vending machine is challenging due to the variety of customer preferences and random breakdown in service. In this paper, we present an optimization model for reliable location design of unmanned vending machines, with the goal to minimize total costs and maximize customer satisfaction. We solve the problem through a two-stage approach in order to mine customers preference from their behaviours and improve design reliability. At the first stage, we design a multi-dimensional measurement to mine customers’ preferences and satisfaction based on their behavioural information. At the second stage, we use a clustering method to analyse the set of candidate points from a systematic perspective. Candidate points with similar locations and customer preferences will be clustered into one “demand zone” and the mutual rescue strategy is considered when breakdown occurred. An experimental study is designed based on the proposed approach and solved by combinational genetic algorithm.
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Acknowledgements
The author would like to thank the anonymous reviewers and editors, whose valuable comments and corrections substantially improved this paper.
Funding
This work was supported by the National Nature Science Foundation of China (Grant No. 71872174). Supported by the Outstanding Innovative Talents Cultivation Funded Programs 2020 of Renmin Univertity of China.
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Wang, M., Yao, J. A reliable location design of unmanned vending machines based on customer satisfaction. Electron Commer Res 23, 541–575 (2023). https://doi.org/10.1007/s10660-021-09479-8
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DOI: https://doi.org/10.1007/s10660-021-09479-8