Adaptive Large Neighborhood Search Metaheuristic for the Capacitated Vehicle Routing Problem with Parcel Lockers

IF 3.6 Q2 MANAGEMENT
Amira Saker, Amr Eltawil, Islam Ali
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引用次数: 0

Abstract

Background: The growth of e-commerce necessitates efficient logistics management to address rising last-mile delivery challenges. To overcome some of the last-mile delivery costs, parcel lockers as a delivery option, can be an alternative solution. This study presents the Capacitated Vehicle Routing Problem with Delivery Options (CVRPDO), which includes locker delivery. Methods: this problem is solved with An Adaptive Large Neighborhood Search (ALNS). The solution suggests some specific destroy and repair operators and integrates them with various selection schemes. The proposed method results are compared with the exact solution of the MIP model of the problem for validation. Results: Objective function values improved by 25%, 30%, 7%, 5%, and 6% for 1000, 800, 600, 400, and 200 customers, respectively, when using a 120-s ALNS runtime compared to the MIP model with a 3-h runtime. Conclusions: the CVRPDO problem involves creating a set of routes for ve-hicles that visit each customer at their delivery location or deliver their parcels to one of the lockers. These routes should respect the capacity of each vehicle and locker while minimizing the total routing costs and the number of utilized vehicles. The problem is resolved by ALNS algorithm, which outperformed the MIP model.
基于自适应大邻域搜索的包裹储物柜车辆路径问题元启发式算法
背景:电子商务的发展需要高效的物流管理来应对日益增长的最后一英里交付挑战。为了克服最后一英里的运输成本,包裹储物柜可以作为一种替代解决方案。本研究提出包含储物柜配送选项的有能力车辆路线问题(CVRPDO)。方法:采用自适应大邻域搜索(ALNS)方法解决该问题。该方案提出了一些具体的破坏和修复操作,并将其与各种选择方案相结合。将该方法的结果与问题的MIP模型的精确解进行了比较,以验证该方法的有效性。结果:与使用3小时运行时间的MIP模型相比,使用120秒ALNS运行时间的1000、800、600、400和200个客户的目标函数值分别提高了25%、30%、7%、5%和6%。结论:CVRPDO问题涉及到为五辆车创建一组路线,这些车在送货地点访问每个客户,或者将他们的包裹送到其中一个储物柜。这些路线应尊重每辆车和储物柜的容量,同时尽量减少总路线成本和使用车辆的数量。用ALNS算法解决了该问题,该算法优于MIP模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Logistics-Basel
Logistics-Basel Multiple-
CiteScore
6.60
自引率
0.00%
发文量
0
审稿时长
11 weeks
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