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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| Vydané v: | European journal of operational research Ročník 302; číslo 3; s. 1113 - 1127 |
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| Jazyk: | English |
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Elsevier B.V
01.11.2022
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| ISSN: | 0377-2217, 1872-6860 |
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| Abstract | •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. |
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| AbstractList | •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. |
| Author | Yamada, Tadashi Qureshi, Ali Gul Wu, Yuehui |
| Author_xml | – sequence: 1 givenname: Yuehui orcidid: 0000-0002-1755-3360 surname: Wu fullname: Wu, Yuehui email: wu.yuehui.34w@st.kyoto-u.ac.jp organization: Department of Urban Management, Graduate School of Engineering, Kyoto University, Katsura Campus, Nishikyo-ku, Kyoto-shi, Kyoto, 615-8246, Japan – sequence: 2 givenname: Ali Gul surname: Qureshi fullname: Qureshi, Ali Gul email: qureshi.aligul.4c@kyoto-u.ac.jp organization: Department of Urban Management, Graduate School of Engineering, Kyoto University, Katsura Campus, Nishikyo-ku, Kyoto-shi, Kyoto, 615-8246, Japan – sequence: 3 givenname: Tadashi surname: Yamada fullname: Yamada, Tadashi email: yamada.tadashi.2x@kyoto-u.ac.jp organization: Department of Urban Management, Graduate School of Engineering, Kyoto University, Katsura Campus, Nishikyo-ku, Kyoto-shi, Kyoto, 615-8246, Japan |
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| Cites_doi | 10.4028/www.scientific.net/AMM.409-410.1188 10.1016/S0377-2217(98)00395-6 10.1007/BF02564791 10.1002/net.21685 10.1016/j.ejor.2015.06.082 10.1023/A:1018994432663 10.1016/0377-2217(94)90318-2 10.1007/s10479-010-0705-2 10.1016/S0377-2217(87)80007-3 10.1016/j.ejor.2014.04.026 10.1016/j.asoc.2010.05.035 10.1287/trsc.1050.0135 10.1016/j.cie.2017.12.020 10.1016/j.cor.2010.07.014 10.1016/j.ejor.2004.09.047 10.1155/2015/525980 10.1016/j.ejor.2013.12.021 10.1016/j.cie.2013.01.012 10.1016/j.apm.2013.02.035 10.1016/j.cor.2006.07.002 10.1016/j.tre.2017.10.004 10.1016/j.ijpe.2003.12.002 10.1016/j.cor.2014.04.014 10.1080/00207543.2019.1693652 10.1016/j.cor.2012.04.007 10.1016/j.tre.2011.04.009 10.1016/j.cie.2019.05.038 |
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| Keywords | Hub location routing problem Intra-city express Location Mixed integer programming model Meta-heuristics |
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| Snippet | •We model a new variant of multi-allocation hub location routing problem.•An adaptive large neighborhood algorithm is introduced to solve the problem.•The... |
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| SubjectTerms | Hub location routing problem Intra-city express Location Meta-heuristics Mixed integer programming model |
| Title | Adaptive large neighborhood decomposition search algorithm for multi-allocation hub location routing problem |
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