A variable neighborhood search algorithm for the (r∣p) hub–centroid problem under the price war
This study considers the ( r ∣ p ) hub–centroid problem under the price war, which was recently proposed in the literature. The objective is profit maximization by choosing the best hub and spoke topology, with the corresponding price structure, in a leader–follower setting. Because this bi–level op...
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| Published in | Journal of global optimization Vol. 83; no. 3; pp. 405 - 444 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
Springer US
01.07.2022
Springer Springer Nature B.V |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0925-5001 1573-2916 |
| DOI | 10.1007/s10898-021-01036-9 |
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| Abstract | This study considers the
(
r
∣
p
)
hub–centroid problem under the price war, which was recently proposed in the literature. The objective is profit maximization by choosing the best hub and spoke topology, with the corresponding price structure, in a leader–follower setting. Because this bi–level optimization problem is NP–hard, the use of metaheuristics is a natural choice for solving real–size instances. A variable neighborhood search algorithm is designed as a solution approach for the leader. The characterization of optimal routes under the price equilibrium is given in order to simplify and improve the algorithm. When it comes to the follower, we have shown how to reformulate in a linear fashion the initial non–linear model. The computational experiments are conducted on the CAB instances. The results of these experiments are thoroughly discussed, highlighting the effects of different parameters and providing some interesting managerial insights. |
|---|---|
| AbstractList | This study considers the
(
r
∣
p
)
hub–centroid problem under the price war, which was recently proposed in the literature. The objective is profit maximization by choosing the best hub and spoke topology, with the corresponding price structure, in a leader–follower setting. Because this bi–level optimization problem is NP–hard, the use of metaheuristics is a natural choice for solving real–size instances. A variable neighborhood search algorithm is designed as a solution approach for the leader. The characterization of optimal routes under the price equilibrium is given in order to simplify and improve the algorithm. When it comes to the follower, we have shown how to reformulate in a linear fashion the initial non–linear model. The computational experiments are conducted on the CAB instances. The results of these experiments are thoroughly discussed, highlighting the effects of different parameters and providing some interesting managerial insights. This study considers the [Formula omitted] hub-centroid problem under the price war, which was recently proposed in the literature. The objective is profit maximization by choosing the best hub and spoke topology, with the corresponding price structure, in a leader-follower setting. Because this bi-level optimization problem is NP-hard, the use of metaheuristics is a natural choice for solving real-size instances. A variable neighborhood search algorithm is designed as a solution approach for the leader. The characterization of optimal routes under the price equilibrium is given in order to simplify and improve the algorithm. When it comes to the follower, we have shown how to reformulate in a linear fashion the initial non-linear model. The computational experiments are conducted on the CAB instances. The results of these experiments are thoroughly discussed, highlighting the effects of different parameters and providing some interesting managerial insights. This study considers the (r∣p) hub–centroid problem under the price war, which was recently proposed in the literature. The objective is profit maximization by choosing the best hub and spoke topology, with the corresponding price structure, in a leader–follower setting. Because this bi–level optimization problem is NP–hard, the use of metaheuristics is a natural choice for solving real–size instances. A variable neighborhood search algorithm is designed as a solution approach for the leader. The characterization of optimal routes under the price equilibrium is given in order to simplify and improve the algorithm. When it comes to the follower, we have shown how to reformulate in a linear fashion the initial non–linear model. The computational experiments are conducted on the CAB instances. The results of these experiments are thoroughly discussed, highlighting the effects of different parameters and providing some interesting managerial insights. |
| Audience | Academic |
| Author | Plyasunov, Aleksandr V. Čvokić, Dimitrije D. Savić, Aleksandar Kochetov, Yury A. |
| Author_xml | – sequence: 1 givenname: Dimitrije D. orcidid: 0000-0001-7975-4224 surname: Čvokić fullname: Čvokić, Dimitrije D. email: dimitrije.cvokic@pmf.unibl.org organization: Faculty of Natural Sciences and Mathematics, University of Banja Luka – sequence: 2 givenname: Yury A. surname: Kochetov fullname: Kochetov, Yury A. organization: Sobolev Institute of Mathematics, Novosibirsk State University – sequence: 3 givenname: Aleksandr V. surname: Plyasunov fullname: Plyasunov, Aleksandr V. organization: Sobolev Institute of Mathematics, Novosibirsk State University – sequence: 4 givenname: Aleksandar surname: Savić fullname: Savić, Aleksandar organization: Faculty of Mathematics, University of Belgrade |
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| CitedBy_id | crossref_primary_10_1007_s10898_022_01186_4 crossref_primary_10_1007_s11590_022_01924_3 |
| Cites_doi | 10.1016/j.ins.2015.07.044 10.1007/s11590-015-0867-6 10.1016/j.ejor.2007.06.008 10.1007/s40314-019-1025-z 10.1142/S021926591940005X 10.1287/trsc.1120.0410 10.2307/1911955 10.2307/2224214 10.1134/S0005117914040080 10.1016/j.cor.2011.05.007 10.1134/S0005117914040110 10.1007/s10589-008-9170-0 10.1007/s10479-017-2508-1 10.1007/s11067-014-9276-0 10.2298/FIL2008463C 10.1134/S1990478915030102 10.1016/S0305-0548(02)00024-2 10.1016/S0453-4514(01)80019-3 10.1016/j.ejor.2015.09.008 10.1111/j.1937-5956.2007.tb00168.x 10.1016/S0305-0548(97)00031-2 10.1016/j.ejor.2013.06.006 10.1016/S0377-2217(87)80007-3 10.1016/j.cie.2013.01.012 10.1109/MCSE.2007.55 10.1007/978-1-4419-7572-0_12 10.1007/978-3-030-22629-9_10 10.1007/978-3-319-44914-2_2 |
| ContentType | Journal Article |
| Copyright | The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021 COPYRIGHT 2022 Springer The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021. |
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| Keywords | Competitive hub location Variable neighborhood search Pricing Reformulation 90B80 90C90 90C59 91B06 90B06 |
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hub–centroid problem under the price war, which was recently proposed in the literature. The objective is profit... This study considers the [Formula omitted] hub-centroid problem under the price war, which was recently proposed in the literature. The objective is profit... This study considers the (r∣p) hub–centroid problem under the price war, which was recently proposed in the literature. The objective is profit maximization by... |
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| SubjectTerms | Algorithms Centroids Competition Computer Science Equilibrium Experiments Game theory Heuristic methods Mathematics Mathematics and Statistics Operations Research/Decision Theory Optimization Price wars Profit maximization Profits Real Functions Search algorithms Topology |
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| Title | A variable neighborhood search algorithm for the (r∣p) hub–centroid problem under the price war |
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