Using GA for Locating Post-disaster Field Hospitals: The Case of Istanbul

Yesim Komurcu; Seda Yanik

doi:10.1007/978-3-030-51156-2_170

Using GA for Locating Post-disaster Field Hospitals: The Case of Istanbul

Yesim Komurcu, Seda Yanik^*

^*Corresponding author for this work

Department of Industrial Engineering

Halic University

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

Abstract

Most of the post-disaster losses occur due to the lack of humanitarian relief planning or inadequate implementations. Locating temporary field hospitals (FHs) and assignment of the injured people to the hospitals are key issues in natural disaster management. The capacities of existing emergency units of hospitals (EH) are expected to be not enough for the injured people in case of a serious earthquake in Istanbul. Thus, the FHs which will serve as additional capacity are needed. The objectives of this study are to minimize the total travel cost and the total cost of establishing FHs in order to respond to all of the injured as quickly as possible. To this aim, a heuristic solution methodology, genetic algorithm (GA) is developed in MATLAB. Different crossover and replacement strategies have been tested in order to improve the performance of the algorithm. In the experimental study, the performances of different GAs strategies are compared using experimental datasets where optimal results are known. According to the result of the comparison, the best GA is selected and applied the for the real Istanbul dataset.

Original language	English
Title of host publication	Intelligent and Fuzzy Techniques
Subtitle of host publication	Smart and Innovative Solutions - Proceedings of the INFUS 2020 Conference
Editors	Cengiz Kahraman, Sezi Cevik Onar, Basar Oztaysi, Irem Ucal Sari, Selcuk Cebi, A. Cagri Tolga
Publisher	Springer
Pages	1464-1472
Number of pages	9
ISBN (Print)	9783030511555
DOIs	https://doi.org/10.1007/978-3-030-51156-2_170
Publication status	Published - 2021
Event	International Conference on Intelligent and Fuzzy Systems, INFUS 2020 - Istanbul, Turkey Duration: 21 Jul 2020 → 23 Jul 2020

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	1197 AISC
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Conference

Conference	International Conference on Intelligent and Fuzzy Systems, INFUS 2020
Country/Territory	Turkey
City	Istanbul
Period	21/07/20 → 23/07/20

Bibliographical note

Publisher Copyright:
© 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

Genetic algorithm
Humanitarian relief
Location-allocation

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-030-51156-2_170

Cite this

Komurcu, Y., & Yanik, S. (2021). Using GA for Locating Post-disaster Field Hospitals: The Case of Istanbul. In C. Kahraman, S. Cevik Onar, B. Oztaysi, I. U. Sari, S. Cebi, & A. C. Tolga (Eds.), Intelligent and Fuzzy Techniques: Smart and Innovative Solutions - Proceedings of the INFUS 2020 Conference (pp. 1464-1472). (Advances in Intelligent Systems and Computing; Vol. 1197 AISC). Springer. https://doi.org/10.1007/978-3-030-51156-2_170

Komurcu, Yesim ; Yanik, Seda. / Using GA for Locating Post-disaster Field Hospitals : The Case of Istanbul. Intelligent and Fuzzy Techniques: Smart and Innovative Solutions - Proceedings of the INFUS 2020 Conference. editor / Cengiz Kahraman ; Sezi Cevik Onar ; Basar Oztaysi ; Irem Ucal Sari ; Selcuk Cebi ; A. Cagri Tolga. Springer, 2021. pp. 1464-1472 (Advances in Intelligent Systems and Computing).

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title = "Using GA for Locating Post-disaster Field Hospitals: The Case of Istanbul",

abstract = "Most of the post-disaster losses occur due to the lack of humanitarian relief planning or inadequate implementations. Locating temporary field hospitals (FHs) and assignment of the injured people to the hospitals are key issues in natural disaster management. The capacities of existing emergency units of hospitals (EH) are expected to be not enough for the injured people in case of a serious earthquake in Istanbul. Thus, the FHs which will serve as additional capacity are needed. The objectives of this study are to minimize the total travel cost and the total cost of establishing FHs in order to respond to all of the injured as quickly as possible. To this aim, a heuristic solution methodology, genetic algorithm (GA) is developed in MATLAB. Different crossover and replacement strategies have been tested in order to improve the performance of the algorithm. In the experimental study, the performances of different GAs strategies are compared using experimental datasets where optimal results are known. According to the result of the comparison, the best GA is selected and applied the for the real Istanbul dataset.",

keywords = "Genetic algorithm, Humanitarian relief, Location-allocation",

author = "Yesim Komurcu and Seda Yanik",

note = "Publisher Copyright: {\textcopyright} 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.; International Conference on Intelligent and Fuzzy Systems, INFUS 2020 ; Conference date: 21-07-2020 Through 23-07-2020",

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Komurcu, Y & Yanik, S 2021, Using GA for Locating Post-disaster Field Hospitals: The Case of Istanbul. in C Kahraman, S Cevik Onar, B Oztaysi, IU Sari, S Cebi & AC Tolga (eds), Intelligent and Fuzzy Techniques: Smart and Innovative Solutions - Proceedings of the INFUS 2020 Conference. Advances in Intelligent Systems and Computing, vol. 1197 AISC, Springer, pp. 1464-1472, International Conference on Intelligent and Fuzzy Systems, INFUS 2020, Istanbul, Turkey, 21/07/20. https://doi.org/10.1007/978-3-030-51156-2_170

Using GA for Locating Post-disaster Field Hospitals: The Case of Istanbul. / Komurcu, Yesim; Yanik, Seda.
Intelligent and Fuzzy Techniques: Smart and Innovative Solutions - Proceedings of the INFUS 2020 Conference. ed. / Cengiz Kahraman; Sezi Cevik Onar; Basar Oztaysi; Irem Ucal Sari; Selcuk Cebi; A. Cagri Tolga. Springer, 2021. p. 1464-1472 (Advances in Intelligent Systems and Computing; Vol. 1197 AISC).

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

TY - GEN

T1 - Using GA for Locating Post-disaster Field Hospitals

T2 - International Conference on Intelligent and Fuzzy Systems, INFUS 2020

AU - Komurcu, Yesim

AU - Yanik, Seda

PY - 2021

Y1 - 2021

N2 - Most of the post-disaster losses occur due to the lack of humanitarian relief planning or inadequate implementations. Locating temporary field hospitals (FHs) and assignment of the injured people to the hospitals are key issues in natural disaster management. The capacities of existing emergency units of hospitals (EH) are expected to be not enough for the injured people in case of a serious earthquake in Istanbul. Thus, the FHs which will serve as additional capacity are needed. The objectives of this study are to minimize the total travel cost and the total cost of establishing FHs in order to respond to all of the injured as quickly as possible. To this aim, a heuristic solution methodology, genetic algorithm (GA) is developed in MATLAB. Different crossover and replacement strategies have been tested in order to improve the performance of the algorithm. In the experimental study, the performances of different GAs strategies are compared using experimental datasets where optimal results are known. According to the result of the comparison, the best GA is selected and applied the for the real Istanbul dataset.

AB - Most of the post-disaster losses occur due to the lack of humanitarian relief planning or inadequate implementations. Locating temporary field hospitals (FHs) and assignment of the injured people to the hospitals are key issues in natural disaster management. The capacities of existing emergency units of hospitals (EH) are expected to be not enough for the injured people in case of a serious earthquake in Istanbul. Thus, the FHs which will serve as additional capacity are needed. The objectives of this study are to minimize the total travel cost and the total cost of establishing FHs in order to respond to all of the injured as quickly as possible. To this aim, a heuristic solution methodology, genetic algorithm (GA) is developed in MATLAB. Different crossover and replacement strategies have been tested in order to improve the performance of the algorithm. In the experimental study, the performances of different GAs strategies are compared using experimental datasets where optimal results are known. According to the result of the comparison, the best GA is selected and applied the for the real Istanbul dataset.

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KW - Humanitarian relief

KW - Location-allocation

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AN - SCOPUS:85088750755

SN - 9783030511555

T3 - Advances in Intelligent Systems and Computing

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A2 - Kahraman, Cengiz

A2 - Cevik Onar, Sezi

A2 - Oztaysi, Basar

A2 - Sari, Irem Ucal

A2 - Cebi, Selcuk

A2 - Tolga, A. Cagri

PB - Springer

Y2 - 21 July 2020 through 23 July 2020

ER -

Komurcu Y, Yanik S. Using GA for Locating Post-disaster Field Hospitals: The Case of Istanbul. In Kahraman C, Cevik Onar S, Oztaysi B, Sari IU, Cebi S, Tolga AC, editors, Intelligent and Fuzzy Techniques: Smart and Innovative Solutions - Proceedings of the INFUS 2020 Conference. Springer. 2021. p. 1464-1472. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-030-51156-2_170

Using GA for Locating Post-disaster Field Hospitals: The Case of Istanbul

Abstract

Publication series

Conference

Bibliographical note

Keywords

UN SDGs

Access to Document

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