Site selection of the Colombian antarctic research station based on fuzzy-topsis algorithm

By 2025 the Republic of Colombia aims to be an advisory member of the Antarctic Treaty System (ATS) and the installation of a scientific station is necessary to upscale the scientific capabilities. The aim of this paper is showing the results of the implementation of a Fuzzy TOPSIS algorithm for sit...

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Autores:
Coronado-Hernandez, Jairo R.
Rios-Angulo, Wilson A.
Segovia, Camilo
Urrego-Rubio, Diana C.
Romero-Conrado, Alfonso R.
Tipo de recurso:
Article of journal
Fecha de publicación:
2020
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
eng
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/8046
Acceso en línea:
https://hdl.handle.net/11323/8046
https://doi.org/10.1007/978-3-030-53956-6_60
https://repositorio.cuc.edu.co/
Palabra clave:
Site selection
Fuzzy TOPSIS
Antarctic station
Rights
openAccess
License
CC0 1.0 Universal
id RCUC2_5b94c69a40a0522dac875d3ccdebee36
oai_identifier_str oai:repositorio.cuc.edu.co:11323/8046
network_acronym_str RCUC2
network_name_str REDICUC - Repositorio CUC
repository_id_str
dc.title.spa.fl_str_mv Site selection of the Colombian antarctic research station based on fuzzy-topsis algorithm
title Site selection of the Colombian antarctic research station based on fuzzy-topsis algorithm
spellingShingle Site selection of the Colombian antarctic research station based on fuzzy-topsis algorithm
Site selection
Fuzzy TOPSIS
Antarctic station
title_short Site selection of the Colombian antarctic research station based on fuzzy-topsis algorithm
title_full Site selection of the Colombian antarctic research station based on fuzzy-topsis algorithm
title_fullStr Site selection of the Colombian antarctic research station based on fuzzy-topsis algorithm
title_full_unstemmed Site selection of the Colombian antarctic research station based on fuzzy-topsis algorithm
title_sort Site selection of the Colombian antarctic research station based on fuzzy-topsis algorithm
dc.creator.fl_str_mv Coronado-Hernandez, Jairo R.
Rios-Angulo, Wilson A.
Segovia, Camilo
Urrego-Rubio, Diana C.
Romero-Conrado, Alfonso R.
dc.contributor.author.spa.fl_str_mv Coronado-Hernandez, Jairo R.
Rios-Angulo, Wilson A.
Segovia, Camilo
Urrego-Rubio, Diana C.
Romero-Conrado, Alfonso R.
dc.subject.spa.fl_str_mv Site selection
Fuzzy TOPSIS
Antarctic station
topic Site selection
Fuzzy TOPSIS
Antarctic station
description By 2025 the Republic of Colombia aims to be an advisory member of the Antarctic Treaty System (ATS) and the installation of a scientific station is necessary to upscale the scientific capabilities. The aim of this paper is showing the results of the implementation of a Fuzzy TOPSIS algorithm for site selection of the Colombian Antarctic Scientific Station. A three-phase methodology was AQ1 proposed, and the obtained results allowed to identify the optimum location for the station, considering key success factors and regulatory constraints.
publishDate 2020
dc.date.issued.none.fl_str_mv 2020-10
dc.date.accessioned.none.fl_str_mv 2021-03-18T17:20:30Z
dc.date.available.none.fl_str_mv 2021-03-18T17:20:30Z
dc.type.spa.fl_str_mv Artículo de revista
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dc.type.coar.spa.fl_str_mv http://purl.org/coar/resource_type/c_6501
dc.type.content.spa.fl_str_mv Text
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dc.identifier.issn.spa.fl_str_mv 03029743
16113349
dc.identifier.uri.spa.fl_str_mv https://hdl.handle.net/11323/8046
dc.identifier.doi.spa.fl_str_mv https://doi.org/10.1007/978-3-030-53956-6_60
dc.identifier.instname.spa.fl_str_mv Corporación Universidad de la Costa
dc.identifier.reponame.spa.fl_str_mv REDICUC - Repositorio CUC
dc.identifier.repourl.spa.fl_str_mv https://repositorio.cuc.edu.co/
identifier_str_mv 03029743
16113349
Corporación Universidad de la Costa
REDICUC - Repositorio CUC
url https://hdl.handle.net/11323/8046
https://doi.org/10.1007/978-3-030-53956-6_60
https://repositorio.cuc.edu.co/
dc.language.iso.none.fl_str_mv eng
language eng
dc.relation.references.spa.fl_str_mv 1. Zadeh, L.A.: Fuzzy sets. Inf. Control 8, 338–353 (1965)
2. Hwang, C.-L., Yoon, K.: Multiple Attribute Decision Making. Springer, Heidelberg (1981). https://doi.org/10.1007/978-3-642-48318-9
3. Sindhu, S., Nehra, V., Luthra, S.: Investigation of feasibility study of solar farms deployment using hybrid AHP-TOPSIS analysis: case study of India. Renew. Sustain. Energy Rev. 73, 496–511 (2017)
4. Perera, A.T.D., Nik, V.M., Mauree, D., Scartezzini, J.-L.: An integrated approach to design site specific distributed electrical hubs combining optimization, multi-criterion assessment and decision making. Energy 134, 103–120 (2017)
5. Zamri, N., Ahmad, F., Rose, A.N.M., Makhtar, M.: A fuzzy TOPSIS with Z-numbers approach for evaluation on accident at the construction site. In: Herawan, T., Ghazali, R., Nawi, N.M., Deris, M.M. (eds.) SCDM 2016. AISC, vol. 549, pp. 41–50. Springer, Cham (2017). https:// doi.org/10.1007/978-3-319-51281-5_5
6. Bostanci, B., Bakir, N.Y., Doˇgan, U., Göngör, M.K.: Research on GIS-aided housing satisfaction using fuzzy decision-making techniques—Bulanik karar verme teknikleri ile CBS destekli konut memnuniyeti ara¸stirmasi. J. Fac. Eng. Archit. Gazi Univ. 32, 1193–1207 (2017)
7. Pahari, S., Ghosh, D., Pal, A.: An online review-based hotel selection process using intuitionistic fuzzy TOPSIS method. In: Pattnaik, P.K., Rautaray, S.S., Das, H., Nayak, J. (eds.) Progress in Computing, Analytics and Networking. AISC, vol. 710, pp. 203–214. Springer, Singapore (2018). https://doi.org/10.1007/978-981-10-7871-2_20
8. Wang, C.-N., Nguyen, V.T., Thai, H.T.N., Duong, D.H.: Multi-criteria decision making (MCDM) approaches for solar power plant location selection in Viet Nam. Energies 11, 1504 (2018)
9. Hanine, M., Boutkhoum, O., Tikniouine, A., Agouti, T.: An application of OLAP/GIS-Fuzzy AHP-TOPSIS methodology for decision making: location selection for landfill of industrial wastes as a case study. KSCE J. Civ. Eng. 21, 2074–2084 (2017)
10. Polat, G., Eray, E., Bingol, B.N.: An integrated fuzzy MCGDM approach for supplier selection problem. J. Civ. Eng. Manag. 23, 926–942 (2017)
11. Deveci, M., Canıtez, F., Göka¸sar, I.: WASPAS and TOPSIS based interval type-2 fuzzy MCDM method for a selection of a car sharing station. Sustain. Cities Soc. 41, 777–791 (2018)
12. Trivedi, A., Singh, A.: Prioritizing emergency shelter areas using hybrid multi-criteria decision approach: a case study. J. Multi-Criteria Decis. Anal. 24, 133–145 (2017)
13. Daneshvar Rouyendegh, B., Yildizbasi, A., Arikan, Ü.Z.B.: Using intuitionistic fuzzy TOPSIS in site selection of wind power plants in Turkey. Adv. Fuzzy Syst. 2018, 14 (2018)
14. Darani, S.K., Eslami, A.A., Jabbari, M., Asefi, H.: Parking lot site selection using a fuzzy AHP-TOPSIS framework in Tuyserkan, Iran. J. Urban Plan. Dev. 144 (2018)
15. Noori, A., Bonakdari, H., Morovati, K., Gharabaghi, B.: The optimal dam site selection using a group decision-making method through fuzzy TOPSIS model. Environ. Syst. Decis. 38, 471–488 (2018)
16. Kutlu Gündoˇgdu, F., Kahraman, C.: A novel VIKOR method using spherical fuzzy sets and its application to warehouse site selection. J. Intell. Fuzzy Syst. 37, 1197–1211 (2019)
17. Erba¸s, M., Kabak, M., Özceylan, E., Çetinkaya, C.: Optimal siting of electric vehicle charging stations: a GIS-based fuzzy Multi-Criteria Decision Analysis. Energy 163, 1017–1031 (2018)
18. Wang, C.-N., Huang, Y.-F., Chai, Y.-C., Nguyen, V.T.: A Multi-Criteria Decision Making (MCDM) for renewable energy plants location selection in Vietnam under a fuzzy environment. Appl. Sci. 8, 2069 (2018)
19. Mayaki, E.A., Adedipe, O., Lawal, S.A.: Multi-criteria evaluation of the appropriate offshore wind farm location in Nigeria. In: IOP Conference Series: Materials Science and Engineering (2018)
20. Drakaki, M., Gören, H.G., Tzionas, P.: Comparison of fuzzy multi criteria decision making approaches in an intelligent multi-agent system for refugee siting. In: Swi˛ ´ atek, J., Borzemski, L., Wilimowska, Z. (eds.) ISAT 2018. AISC, vol. 853, pp. 361–370. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-99996-8_33
21. Bakhtavar, E., Yousefi, S., Jafarpour, A.: Evaluation of shaft locations in underground mines: Fuzzy multiobjective optimization by ratio analysis with fuzzy cognitive map weights. J. South. Afr. Inst. Min. Metall. 119, 855–864 (2019)
22. Seker, S., Aydin, N.: Hydrogen production facility location selection for Black Sea using entropy based TOPSIS under IVPF environment. Int. J. Hydrogen Energy 45, 15855–15868 (2020)
23. Liang, X., Zhang, R., Liu, C.: Location analysis of regional disaster relief material reserve center: a case study in Sichuan Province, China. In: IEEE International Conference on Industrial Engineering and Engineering Management, pp. 1588–1592 (2019)
24. Mohsin, M., Zhang, J., Saidur, R., Sun, H., Sait, S.M.: Economic assessment and ranking of wind power potential using fuzzy-TOPSIS approach. Environ. Sci. Pollut. Res. 26, 22494– 22511 (2019)
25. Wang, B., Xie, H.-L., Ren, H.-Y., Li, X., Chen, L., Wu, B.-C.: Application of AHP, TOPSIS, and TFNs to plant selection for phytoremediation of petroleum-contaminated soils in shale gas and oil fields. J. Clean. Prod. 233, 13–22 (2019)
26. Yildiz, A., Ayyildiz, E., Taskin Gumus, A., Ozkan, C.: A modified balanced scorecard based hybrid pythagorean fuzzy AHP-topsis methodology for ATM site selection problem. Int. J. Inf. Technol. Decis. Mak. 19, 365–384 (2020)
27. Erdin, C., Akba¸s, H.E.: A comparative analysis of fuzzy TOPSIS and geographic information systems (GIS) for the location selection of shopping malls: a case study from Turkey. Sustainability 11, 3837 (2019)
28. Ortiz-Barrios, M., Nugent, C., Cleland, I., Donnelly, M., Verikas, A.: Selecting the most suitable classification algorithm for supporting assistive technology adoption for people with dementia: a multicriteria framework. J. Multi-Criteria Decis. Anal. 27, 20–38 (2019)
29. León, O.P.: Logística Urbana desde la perspectiva del Agente Generador de Viajes. INGE CUC 15, 45–62 (2019)
30. Restrepo, J.E., Neira Rodado, D., Viloria Silva, A.: Multicriteria strategic approach for the selection of concrete suppliers in a construction company in Colombia. In: Saeed, K., Dvorský, J. (eds.) CISIM 2020. LNCS, vol. 12133, pp. 184–194. Springer, Cham (2020). https://doi. org/10.1007/978-3-030-47679-3_16
31. Yava¸so˘glu, H.H., et al.: Site selection of the turkish antarctic research station using analytic hierarchy process. Polar Sci. 22, 1–12 (2019)
32. Pang, X., Liu, H., Zhao, X.: Selecting suitable sites for an Antarctic research station: a case for a new Chinese research station. Antarct. Sci. 26, 479–490 (2014)
33. Correa, M.: ¿A qué volvemos a la Antártida?. https://www.elcolombiano.com/colombia/exp edicion-a-la-antartida-que-es-LK7862836
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spelling Coronado-Hernandez, Jairo R.Rios-Angulo, Wilson A.Segovia, CamiloUrrego-Rubio, Diana C.Romero-Conrado, Alfonso R.2021-03-18T17:20:30Z2021-03-18T17:20:30Z2020-100302974316113349https://hdl.handle.net/11323/8046https://doi.org/10.1007/978-3-030-53956-6_60Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/By 2025 the Republic of Colombia aims to be an advisory member of the Antarctic Treaty System (ATS) and the installation of a scientific station is necessary to upscale the scientific capabilities. The aim of this paper is showing the results of the implementation of a Fuzzy TOPSIS algorithm for site selection of the Colombian Antarctic Scientific Station. A three-phase methodology was AQ1 proposed, and the obtained results allowed to identify the optimum location for the station, considering key success factors and regulatory constraints.Coronado-Hernandez, Jairo R.-will be generated-orcid-0000-0003-4360-6128-600Rios-Angulo, Wilson A.Segovia, Camilo-will be generated-orcid-0000-0001-9554-5844-600Urrego-Rubio, Diana C.-will be generated-orcid-0000-0003-4181-3342-600Romero-Conrado, Alfonso R.-will be generated-orcid-0000-0003-4603-0785-600application/pdfengCorporación Universidad de la CostaCC0 1.0 Universalhttp://creativecommons.org/publicdomain/zero/1.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Lecture Notes in Computer Sciencehttps://link.springer.com/chapter/10.1007%2F978-3-030-53956-6_60Site selectionFuzzy TOPSISAntarctic stationSite selection of the Colombian antarctic research station based on fuzzy-topsis algorithmArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Textinfo:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/acceptedVersion1. Zadeh, L.A.: Fuzzy sets. Inf. Control 8, 338–353 (1965)2. Hwang, C.-L., Yoon, K.: Multiple Attribute Decision Making. Springer, Heidelberg (1981). https://doi.org/10.1007/978-3-642-48318-93. Sindhu, S., Nehra, V., Luthra, S.: Investigation of feasibility study of solar farms deployment using hybrid AHP-TOPSIS analysis: case study of India. Renew. Sustain. Energy Rev. 73, 496–511 (2017)4. Perera, A.T.D., Nik, V.M., Mauree, D., Scartezzini, J.-L.: An integrated approach to design site specific distributed electrical hubs combining optimization, multi-criterion assessment and decision making. Energy 134, 103–120 (2017)5. Zamri, N., Ahmad, F., Rose, A.N.M., Makhtar, M.: A fuzzy TOPSIS with Z-numbers approach for evaluation on accident at the construction site. In: Herawan, T., Ghazali, R., Nawi, N.M., Deris, M.M. (eds.) SCDM 2016. AISC, vol. 549, pp. 41–50. Springer, Cham (2017). https:// doi.org/10.1007/978-3-319-51281-5_56. Bostanci, B., Bakir, N.Y., Doˇgan, U., Göngör, M.K.: Research on GIS-aided housing satisfaction using fuzzy decision-making techniques—Bulanik karar verme teknikleri ile CBS destekli konut memnuniyeti ara¸stirmasi. J. Fac. Eng. Archit. Gazi Univ. 32, 1193–1207 (2017)7. Pahari, S., Ghosh, D., Pal, A.: An online review-based hotel selection process using intuitionistic fuzzy TOPSIS method. In: Pattnaik, P.K., Rautaray, S.S., Das, H., Nayak, J. (eds.) Progress in Computing, Analytics and Networking. AISC, vol. 710, pp. 203–214. Springer, Singapore (2018). https://doi.org/10.1007/978-981-10-7871-2_208. Wang, C.-N., Nguyen, V.T., Thai, H.T.N., Duong, D.H.: Multi-criteria decision making (MCDM) approaches for solar power plant location selection in Viet Nam. Energies 11, 1504 (2018)9. Hanine, M., Boutkhoum, O., Tikniouine, A., Agouti, T.: An application of OLAP/GIS-Fuzzy AHP-TOPSIS methodology for decision making: location selection for landfill of industrial wastes as a case study. KSCE J. Civ. Eng. 21, 2074–2084 (2017)10. Polat, G., Eray, E., Bingol, B.N.: An integrated fuzzy MCGDM approach for supplier selection problem. J. Civ. Eng. Manag. 23, 926–942 (2017)11. Deveci, M., Canıtez, F., Göka¸sar, I.: WASPAS and TOPSIS based interval type-2 fuzzy MCDM method for a selection of a car sharing station. Sustain. Cities Soc. 41, 777–791 (2018)12. Trivedi, A., Singh, A.: Prioritizing emergency shelter areas using hybrid multi-criteria decision approach: a case study. J. Multi-Criteria Decis. Anal. 24, 133–145 (2017)13. Daneshvar Rouyendegh, B., Yildizbasi, A., Arikan, Ü.Z.B.: Using intuitionistic fuzzy TOPSIS in site selection of wind power plants in Turkey. Adv. Fuzzy Syst. 2018, 14 (2018)14. Darani, S.K., Eslami, A.A., Jabbari, M., Asefi, H.: Parking lot site selection using a fuzzy AHP-TOPSIS framework in Tuyserkan, Iran. J. Urban Plan. Dev. 144 (2018)15. Noori, A., Bonakdari, H., Morovati, K., Gharabaghi, B.: The optimal dam site selection using a group decision-making method through fuzzy TOPSIS model. Environ. Syst. Decis. 38, 471–488 (2018)16. Kutlu Gündoˇgdu, F., Kahraman, C.: A novel VIKOR method using spherical fuzzy sets and its application to warehouse site selection. J. Intell. Fuzzy Syst. 37, 1197–1211 (2019)17. Erba¸s, M., Kabak, M., Özceylan, E., Çetinkaya, C.: Optimal siting of electric vehicle charging stations: a GIS-based fuzzy Multi-Criteria Decision Analysis. Energy 163, 1017–1031 (2018)18. Wang, C.-N., Huang, Y.-F., Chai, Y.-C., Nguyen, V.T.: A Multi-Criteria Decision Making (MCDM) for renewable energy plants location selection in Vietnam under a fuzzy environment. Appl. Sci. 8, 2069 (2018)19. Mayaki, E.A., Adedipe, O., Lawal, S.A.: Multi-criteria evaluation of the appropriate offshore wind farm location in Nigeria. In: IOP Conference Series: Materials Science and Engineering (2018)20. Drakaki, M., Gören, H.G., Tzionas, P.: Comparison of fuzzy multi criteria decision making approaches in an intelligent multi-agent system for refugee siting. In: Swi˛ ´ atek, J., Borzemski, L., Wilimowska, Z. (eds.) ISAT 2018. AISC, vol. 853, pp. 361–370. Springer, Cham (2019). https://doi.org/10.1007/978-3-319-99996-8_3321. Bakhtavar, E., Yousefi, S., Jafarpour, A.: Evaluation of shaft locations in underground mines: Fuzzy multiobjective optimization by ratio analysis with fuzzy cognitive map weights. J. South. Afr. Inst. Min. Metall. 119, 855–864 (2019)22. Seker, S., Aydin, N.: Hydrogen production facility location selection for Black Sea using entropy based TOPSIS under IVPF environment. Int. J. Hydrogen Energy 45, 15855–15868 (2020)23. Liang, X., Zhang, R., Liu, C.: Location analysis of regional disaster relief material reserve center: a case study in Sichuan Province, China. In: IEEE International Conference on Industrial Engineering and Engineering Management, pp. 1588–1592 (2019)24. Mohsin, M., Zhang, J., Saidur, R., Sun, H., Sait, S.M.: Economic assessment and ranking of wind power potential using fuzzy-TOPSIS approach. Environ. Sci. Pollut. Res. 26, 22494– 22511 (2019)25. Wang, B., Xie, H.-L., Ren, H.-Y., Li, X., Chen, L., Wu, B.-C.: Application of AHP, TOPSIS, and TFNs to plant selection for phytoremediation of petroleum-contaminated soils in shale gas and oil fields. J. Clean. Prod. 233, 13–22 (2019)26. Yildiz, A., Ayyildiz, E., Taskin Gumus, A., Ozkan, C.: A modified balanced scorecard based hybrid pythagorean fuzzy AHP-topsis methodology for ATM site selection problem. Int. J. Inf. Technol. Decis. Mak. 19, 365–384 (2020)27. Erdin, C., Akba¸s, H.E.: A comparative analysis of fuzzy TOPSIS and geographic information systems (GIS) for the location selection of shopping malls: a case study from Turkey. Sustainability 11, 3837 (2019)28. Ortiz-Barrios, M., Nugent, C., Cleland, I., Donnelly, M., Verikas, A.: Selecting the most suitable classification algorithm for supporting assistive technology adoption for people with dementia: a multicriteria framework. J. Multi-Criteria Decis. Anal. 27, 20–38 (2019)29. León, O.P.: Logística Urbana desde la perspectiva del Agente Generador de Viajes. INGE CUC 15, 45–62 (2019)30. Restrepo, J.E., Neira Rodado, D., Viloria Silva, A.: Multicriteria strategic approach for the selection of concrete suppliers in a construction company in Colombia. In: Saeed, K., Dvorský, J. (eds.) CISIM 2020. LNCS, vol. 12133, pp. 184–194. Springer, Cham (2020). https://doi. org/10.1007/978-3-030-47679-3_1631. Yava¸so˘glu, H.H., et al.: Site selection of the turkish antarctic research station using analytic hierarchy process. Polar Sci. 22, 1–12 (2019)32. Pang, X., Liu, H., Zhao, X.: Selecting suitable sites for an Antarctic research station: a case for a new Chinese research station. Antarct. Sci. 26, 479–490 (2014)33. Correa, M.: ¿A qué volvemos a la Antártida?. https://www.elcolombiano.com/colombia/exp edicion-a-la-antartida-que-es-LK7862836PublicationORIGINALSite Selection of the Colombian Antarctic Research Station Based on Fuzzy-Topsis Algorithm.pdfSite Selection of the Colombian Antarctic Research Station Based on Fuzzy-Topsis Algorithm.pdfapplication/pdf839797https://repositorio.cuc.edu.co/bitstreams/7cf6056c-be40-41be-a2f9-889e483ec496/download7b00d386f8b336219d120bf48990a6e0MD51CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8701https://repositorio.cuc.edu.co/bitstreams/77c5bdd4-a771-442c-8f3d-ed492ee26e10/download42fd4ad1e89814f5e4a476b409eb708cMD52LICENSElicense.txtlicense.txttext/plain; charset=utf-83196https://repositorio.cuc.edu.co/bitstreams/1b5008da-9d5f-448d-bfdc-6dc7b1ee1d19/downloade30e9215131d99561d40d6b0abbe9badMD53THUMBNAILSite Selection of the Colombian Antarctic Research Station Based on Fuzzy-Topsis Algorithm.pdf.jpgSite Selection of the Colombian Antarctic 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