Cited By
View all- Wang MYao J(2023)Replenishment and delivery optimization for unmanned vending machines service system based on fuzzy clusteringElectronic Commerce Research10.1007/s10660-022-09544-w23:4(2419-2461)Online publication date: 1-Dec-2023
A reliable location design of unmanned vending machines based on customer satisfaction
Authors: Mozhu Wang, 
Jianming YaoAuthors Info & Claims
Jianming YaoAuthors Info & ClaimsPages 541 - 575
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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© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021.
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Kluwer Academic Publishers
United States
Publication History
Published: 07 April 2021
Accepted: 30 March 2021
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- the National Nature Science Foundation of China
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View all- Wang MYao J(2023)Replenishment and delivery optimization for unmanned vending machines service system based on fuzzy clusteringElectronic Commerce Research10.1007/s10660-022-09544-w23:4(2419-2461)Online publication date: 1-Dec-2023
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