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.

由于客户偏好的多样性和服务中的随机故障，无人自动售货机的位置问题具有挑战性。在本文中，我们提出了一种用于自动售货机可靠位置设计的优化模型，其目的是使总成本最小化并最大程度地提高客户满意度。我们通过两个阶段的方法来解决问题，以便从客户的行为中挖掘他们的喜好并提高设计的可靠性。在第一阶段，我们设计了一个多维度量，以根据客户的行为信息挖掘其偏好和满意度。在第二阶段，我们使用聚类方法从系统的角度分析候选点集。具有相似位置和客户偏好的候选点将被聚集到一个“需求区域”，并且在发生故障时会考虑采取互助策略。在此基础上设计了实验研究方法，并通过组合遗传算法进行了求解。