Adaptive Large Neighborhood Decomposition Search Algorithm for Multi-Allocation Hub Location Routing Problem
Adaptive Large Neighborhood Decomposition Search Algorithm for Multi-Allocation Hub Location Routing Problem
复制标题
多分配集线器位置路由问题的自适应大邻域分解搜索算法
DOI：
10.1016/j.ejor.2022.02.002
复制
发表时间：
2022
影响因子：
6.4
通讯作者：
Tadashi Yamada
中科院分区：
文献类型：
--
作者：
Wu Yuehui;Ali Gul Qureshi;Tadashi Yamada
在这项研究中，我们研究了一个多分配枢纽位置路由问题（MAHLRP）的设计城市内的快递服务系统，在该系统中，邮件和包裹流交换的分支办事处的服务提供商通过当地的图尔斯和枢纽。在此应用中，同时处理拾取和交付过程，并考虑枢纽容量和车辆容量。我们提出了一个混合整数规划制定这个变种的问题的第一次，其次是一个元启发式算法，称为自适应大邻域分解搜索，来解决这个问题。所提出的模型和算法也适用于单分配枢纽位置路由问题（SAHLRP）与比较的原因进行了微小的修改。通过澳大利亚邮政数据集生成的实例进行了一系列的数值实验，以检验所提出的模型和算法的SAHLRP和MAHLRP。结果表明，我们的算法优于CPLEX在解决这两个问题，以及应用MAHLRP可以有效地降低运营成本相比，SAHLRP。
In this study, we investigate a multi-allocation hub location routing problem (MAHLRP) for the design of an intra-city express service system, in which flows of mails and parcels are exchanged among the branch offices of the service provider via local tours and hubs. In this application, the pickup and delivery processes are handled simultaneously, and both hub capacity and vehicle capacity are considered. We propose a mixed integer programming formulation for this variant of problem for the first time, followed by a meta-heuristic algorithm, named as adaptive large neighborhood decomposition search, to solve the problem. The proposed model and algorithm are also applied to the single-allocation hub location routing problem (SAHLRP) with minor modifications for comparison reasons. Series of numerical experiments have been conducted on the instances generated from Australian Post data set to test the proposed model and algorithm for both the SAHLRP and the MAHLRP. The results prove that our algorithm outperforms the CPLEX on solving these two problems, as well as that applying the MAHLRP can efficiently reduce the operating cost as compared to the SAHLRP.