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Local Search Approach for the (r|p)-Centroid Problem Under ℓ1 Metric. / Davydov, Ivan; Gusev, Petr.

Variable Neighborhood Search - 7th International Conference, ICVNS 2019, Revised Selected Papers. ed. / Rachid Benmansour; Angelo Sifaleras; Nenad Mladenovic. Springer Gabler, 2020. p. 81-94 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12010 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

Harvard

Davydov, I & Gusev, P 2020, Local Search Approach for the (r|p)-Centroid Problem Under ℓ1 Metric. in R Benmansour, A Sifaleras & N Mladenovic (eds), Variable Neighborhood Search - 7th International Conference, ICVNS 2019, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12010 LNCS, Springer Gabler, pp. 81-94, 7th International Conference on Variable Neighborhood Search, ICVNS 2019, Rabat, Morocco, 03.10.2019. https://doi.org/10.1007/978-3-030-44932-2_6

APA

Davydov, I., & Gusev, P. (2020). Local Search Approach for the (r|p)-Centroid Problem Under ℓ1 Metric. In R. Benmansour, A. Sifaleras, & N. Mladenovic (Eds.), Variable Neighborhood Search - 7th International Conference, ICVNS 2019, Revised Selected Papers (pp. 81-94). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12010 LNCS). Springer Gabler. https://doi.org/10.1007/978-3-030-44932-2_6

Vancouver

Davydov I, Gusev P. Local Search Approach for the (r|p)-Centroid Problem Under ℓ1 Metric. In Benmansour R, Sifaleras A, Mladenovic N, editors, Variable Neighborhood Search - 7th International Conference, ICVNS 2019, Revised Selected Papers. Springer Gabler. 2020. p. 81-94. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-44932-2_6

Author

Davydov, Ivan ; Gusev, Petr. / Local Search Approach for the (r|p)-Centroid Problem Under ℓ1 Metric. Variable Neighborhood Search - 7th International Conference, ICVNS 2019, Revised Selected Papers. editor / Rachid Benmansour ; Angelo Sifaleras ; Nenad Mladenovic. Springer Gabler, 2020. pp. 81-94 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

BibTeX

@inproceedings{3cb9848fe53340579ce5092b4424515a,
title = "Local Search Approach for the (r|p)-Centroid Problem Under ℓ1 Metric",
abstract = "In the-centroid problem, two players, called the Leader and the Follower, open facilities to service customers. We assume that customers are identified with their location on the plane, and facilities can be opened anywhere on the plane. The Leader opens p facilities. Later on, the Follower opens r facilities. Each customer patronizes the closest facility. The distances are calculated according to-metric. The goal is to find the location of the Leader{\textquoteright}s facilities maximizing her market share. We provide the results on the computational complexity of this problem and develop a local search heuristic, based on the VNS framework. Computational experiments on the randomly generated test instances show that the proposed approach performs well.",
keywords = "(R-P)-centroid, Bilevel programming, Facility location, Manhattan metric, Stackelberg game, Variable neighborhood search",
author = "Ivan Davydov and Petr Gusev",
note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 7th International Conference on Variable Neighborhood Search, ICVNS 2019 ; Conference date: 03-10-2019 Through 05-10-2019",
year = "2020",
month = jan,
day = "1",
doi = "10.1007/978-3-030-44932-2_6",
language = "English",
isbn = "9783030449315",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Gabler",
pages = "81--94",
editor = "Rachid Benmansour and Angelo Sifaleras and Nenad Mladenovic",
booktitle = "Variable Neighborhood Search - 7th International Conference, ICVNS 2019, Revised Selected Papers",
address = "Germany",

}

RIS

TY - GEN

T1 - Local Search Approach for the (r|p)-Centroid Problem Under ℓ1 Metric

AU - Davydov, Ivan

AU - Gusev, Petr

N1 - Publisher Copyright: © 2020, Springer Nature Switzerland AG. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.

PY - 2020/1/1

Y1 - 2020/1/1

N2 - In the-centroid problem, two players, called the Leader and the Follower, open facilities to service customers. We assume that customers are identified with their location on the plane, and facilities can be opened anywhere on the plane. The Leader opens p facilities. Later on, the Follower opens r facilities. Each customer patronizes the closest facility. The distances are calculated according to-metric. The goal is to find the location of the Leader’s facilities maximizing her market share. We provide the results on the computational complexity of this problem and develop a local search heuristic, based on the VNS framework. Computational experiments on the randomly generated test instances show that the proposed approach performs well.

AB - In the-centroid problem, two players, called the Leader and the Follower, open facilities to service customers. We assume that customers are identified with their location on the plane, and facilities can be opened anywhere on the plane. The Leader opens p facilities. Later on, the Follower opens r facilities. Each customer patronizes the closest facility. The distances are calculated according to-metric. The goal is to find the location of the Leader’s facilities maximizing her market share. We provide the results on the computational complexity of this problem and develop a local search heuristic, based on the VNS framework. Computational experiments on the randomly generated test instances show that the proposed approach performs well.

KW - (R-P)-centroid

KW - Bilevel programming

KW - Facility location

KW - Manhattan metric

KW - Stackelberg game

KW - Variable neighborhood search

UR - http://www.scopus.com/inward/record.url?scp=85084747744&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-44932-2_6

DO - 10.1007/978-3-030-44932-2_6

M3 - Conference contribution

AN - SCOPUS:85084747744

SN - 9783030449315

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 81

EP - 94

BT - Variable Neighborhood Search - 7th International Conference, ICVNS 2019, Revised Selected Papers

A2 - Benmansour, Rachid

A2 - Sifaleras, Angelo

A2 - Mladenovic, Nenad

PB - Springer Gabler

T2 - 7th International Conference on Variable Neighborhood Search, ICVNS 2019

Y2 - 3 October 2019 through 5 October 2019

ER -

ID: 24312775