论文标题

利润最大化的包裹储物柜位置问题在阈值luce模型下

Profit-Maximizing Parcel Locker Location Problem under Threshold Luce Model

论文作者

Lin, Yun Hui, Wang, Yuan, Lee, Loo Hay, Chew, Ek Peng

论文摘要

电子商务的增长创造了物流服务的越来越复杂。为了保持竞争力,物流和电子商务公司正在探索新模式作为传统送货上门的补充,其中之一就是自助包裹储物柜。本文研究了一个包裹储物柜的位置问题,公司计划通过找到吸引客户的储物柜设施来引入储物柜服务。目的是最大程度地利用利润,计算设施的收入和成本。为了估算收入,我们使用阈值Luce模型(TLM)来预测客户使用更衣服服务的可能性。然后,我们提出了一个组合优化模型,并开发了根据我们广泛的计算实验实际实施的精确解决方案方法。实际上,我们的建模框架概括了基于二项式logit模型(BNL)和多项式Lo​​git模型(MNL)的传统设施位置问题,这两者都对客户的选择集施加了强大而严格的假设。也就是说,他们认为选择集将仅包含一个设施或所有设施。在我们的数值实验中,我们证明,使用BNL和更衣室位置问题中的MNL可能会分别导致悲观和乐观的收入估计。因此,建议的位置决策将是保守的或侵略性的。相比之下,我们提出的模型可以有效地放松这些假设。我们的结果还表明,由于使用MNL而引起的积极决策将产生不必要的高设施成本,而该设施成本无法通过额外的收入来补偿,从而导致损益在各种情况下可能很重要。最后,我们对输入参数进行灵敏度分析,并提取其他含义。

The growth of e-commerce has created increasing complexity in logistics services. To remain competitive, logistics and e-commerce companies are exploring new modes as supplements to traditional home delivery, one of which is the self-service parcel locker. This paper studies a parcel locker location problem where a company plans to introduce the locker service by locating locker facilities to attract customers. The objective is to maximize the profit, accounting for the revenue and the cost of facilities. To estimate the revenue, we use the threshold Luce model (TLM) to predict customers' likelihood of using the locker service. We then propose a combinatorial optimization model and develop exact solution methodologies that are practically implementable according to our extensive computational experiments. In effect, our modeling framework generalizes the traditional facility location problems based on the binomial logit model (BNL) and the multinomial logit model (MNL), both of which impose strong and strict assumptions on the customer's choice sets. That is, they assume that the choice sets will either contain only one facility or all facilities. In our numerical experiment, we demonstrate that using the BNL and the MNL in the locker location problem could lead to, respectively, pessimistic and optimistic revenue estimation. Consequently, the suggested location decisions will be either conservative or aggressive. Our proposed model, by contrast, can effectively relax these assumptions. Our results also reveal that the aggressive decision due to the use of the MNL will incur an unnecessarily high facility cost that cannot be compensated by the additional revenue, leading to profit loss that can be significant in various scenarios. Finally, we conduct sensitivity analysis on the input parameters and draw additional implications.

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