A reliable location design of unmanned vending machines based on customer satisfaction

Mozhu Wang () and Jianming Yao ()
Additional contact information
Mozhu Wang: Renmin University of China
Jianming Yao: Renmin University of China

Electronic Commerce Research, 2023, vol. 23, issue 1, No 21, 575 pages

Abstract: 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.

Keywords: Facility location problem; Unmanned vending machine (UVM); Cluster analysis; Mutual rescue (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10660-021-09479-8 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:elcore:v:23:y:2023:i:1:d:10.1007_s10660-021-09479-8

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10660

DOI: 10.1007/s10660-021-09479-8

Access Statistics for this article

Electronic Commerce Research is currently edited by James Westland

More articles in Electronic Commerce Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().