A variable neighborhood search algorithm for the (r∣ p) hub–centroid problem under the price war

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A variable neighborhood search algorithm for the (r∣ p) hub–centroid problem under the price war. / Čvokić, Dimitrije D.; Kochetov, Yury A.; Plyasunov, Aleksandr V. et al.

In: Journal of Global Optimization, Vol. 83, No. 3, 07.2022, p. 405-444.

Research output: Contribution to journal › Article › peer-review

BibTeX

@article{07311950b577423582484f2800a00926,

title = "A variable neighborhood search algorithm for the (r∣ p) hub–centroid problem under the price war",

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.",

keywords = "Competitive hub location, Pricing, Reformulation, Variable neighborhood search",

author = "{\v C}voki{\'c}, {Dimitrije D.} and Kochetov, {Yury A.} and Plyasunov, {Aleksandr V.} and Aleksandar Savi{\'c}",

note = "Funding Information: The research of the second author was supported by the Russian Foundation for Basic Research, Grant 18-07-00599. The research of the third author was supported by the program of fundamental scientific researches of the SB RAS. The research of the fourth author was partially supported by Serbian Ministry of Education, Science and Technological Development under the Grant No. 174010. Publisher Copyright: {\textcopyright} 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.",

year = "2022",

month = jul,

doi = "10.1007/s10898-021-01036-9",

language = "English",

volume = "83",

pages = "405--444",

journal = "Journal of Global Optimization",

issn = "0925-5001",

publisher = "Springer Netherlands",

number = "3",

}

RIS

TY - JOUR

T1 - A variable neighborhood search algorithm for the (r∣ p) hub–centroid problem under the price war

AU - Čvokić, Dimitrije D.

AU - Kochetov, Yury A.

AU - Plyasunov, Aleksandr V.

AU - Savić, Aleksandar

N1 - Funding Information: The research of the second author was supported by the Russian Foundation for Basic Research, Grant 18-07-00599. The research of the third author was supported by the program of fundamental scientific researches of the SB RAS. The research of the fourth author was partially supported by Serbian Ministry of Education, Science and Technological Development under the Grant No. 174010. Publisher Copyright: © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

PY - 2022/7

Y1 - 2022/7

N2 - 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.

AB - 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.

KW - Competitive hub location

KW - Pricing

KW - Reformulation

KW - Variable neighborhood search

UR - http://www.scopus.com/inward/record.url?scp=85106407853&partnerID=8YFLogxK

U2 - 10.1007/s10898-021-01036-9

DO - 10.1007/s10898-021-01036-9

M3 - Article

AN - SCOPUS:85106407853

VL - 83

SP - 405

EP - 444

JO - Journal of Global Optimization

JF - Journal of Global Optimization

SN - 0925-5001

IS - 3

ER -

ID: 34108937