Adaptive large neighborhood decomposition search algorithm for multi-allocation hub location routing problem

•We model a new variant of multi-allocation hub location routing problem.•An adaptive large neighborhood algorithm is introduced to solve the problem.•The algorithm is also applied to single-allocation version of the problem.•Numerical results prove that the algorithm performs well on benchmark inst...

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Veröffentlicht in:European journal of operational research Jg. 302; H. 3; S. 1113 - 1127
Hauptverfasser: Wu, Yuehui, Qureshi, Ali Gul, Yamada, Tadashi
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier B.V 01.11.2022
Schlagworte:
Hub location routing problem
Intra-city express
Location
Meta-heuristics
Mixed integer programming model
Hub location routing problem
Intra-city express
Location
Mixed integer programming model
Meta-heuristics
ISSN:0377-2217, 1872-6860
Online-Zugang:Volltext
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Zusammenfassung:•We model a new variant of multi-allocation hub location routing problem.•An adaptive large neighborhood algorithm is introduced to solve the problem.•The algorithm is also applied to single-allocation version of the problem.•Numerical results prove that the algorithm performs well on benchmark instances.•The application of multi-allocation can efficiently reduce the operation cost. 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.
ISSN:0377-2217
1872-6860
DOI:10.1016/j.ejor.2022.02.002