Technical gazette, Vol. 31 No. 3, 2024.
Original scientific paper
https://doi.org/10.17559/TV-20230717000807
The Vehicle Routing Problem Considering Customers' Multiple Preferences in Last-Mile Delivery
Shouting Zhao
orcid.org/0009-0002-5296-7654
; Logistics School, Beijing Wuzi University, #321 Fuhe Street, Tongzhou District, Beijing, China
Pu Li
orcid.org/0009-0008-3066-4795
; Logistics School, Beijing Wuzi University, #321 Fuhe Street, Tongzhou District, Beijing, China
*
Qinghua Li
; Department of Logistics Management, Beijing Jiaotong University, No. 3 Shangyuancun, Haidian District, Beijing, China
* Corresponding author.
Abstract
Last-mile delivery plays a crucial role in improving the service level of express delivery, as it involves direct contact with customers. Providing personalized last-mile delivery services is an important means of improving customer satisfaction. Massive consumer data makes it possible to mine customers’ personalized logistics preferences. The paper studies the vehicle routing problem in last-mile delivery considering customers' preferences. The paper first quantifies customers' preferences for delivery time, location, and mode, and obtains preference probabilities based on historical data. Then, an optimization considering customer satisfaction and enterprise delivery costs is established, and a vehicle routing problem model considering customer preferences is proposed. To solve the problem, we designed an adaptive large neighborhood search (ALNS) algorithm with virtual delivery points to solve the problem and proposed specific destroy and repair operators. Through the case analysis of an express delivery company, this article provides the optimal routs and analyzes the customer preferences on each route. In addition, this article explores the impact of the customer preference constraint and complaint constraint on cost and gives the appropriate customer preference constraint and complaint rate constraint from the perspective of cost-saving.
Keywords
ALNS; customer preferences; last-mile delivery; VRP
Hrčak ID:
316355
URI
Publication date:
23.4.2024.
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