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Location selection of medicinal and aromatic plant processing facility with fuzzy EDAS method: Artvin example

Year 2024, Volume: 25 Issue: 1, 136 - 150, 15.05.2024
https://doi.org/10.17474/artvinofd.1453305

Abstract

Climate change, biodiversity and good soil management, together with the rapid population growth in the world, increase the importance of better management and efficient use of such scarce resources. Medicinal and aromatic plants (MAPs) are among these resources and have an economic added value potential. Facility location selection for the processing of MAPs produced directly from nature or through culture is an important strategic decision element, and in general, the facility location selection problem emerges as one of the most fundamental strategic decision-making problems faced by businesses or organizations. To analyze this complex decision-making process, where many factors have minor or significant effects, this study followed the steps of the EDAS (The evaluation based on distance from average solution) methodology, one of the multi-criteria decision-making methods (MCDM). In addition, by taking advantage of the fuzzy theory's ability to deal with uncertainty and incomplete information (here with trapezoidal fuzzy numbers), a significant advantage has been achieved in terms of saving time and resources to solve the problem. In the solution process, three decision-makers evaluated six alternative locations in linguistic terms. A priority order was formed, and the most suitable location (A2- Seyitler Campus) was determined.

References

  • Akram M, Ramzan N, Deveci M (2023) Linguistic pythagorean fuzzy CRITIC-EDAS method for multiple-attribute group decision analysis. Engineering Applications of Artificial Intelligence, 119: 105777.
  • Almutairi K (2022) Determining the appropriate location for renewable hydrogen development using multi‐criteria decision‐making approaches. International Journal of Energy Research, 46(5): 5876-5895.
  • Athawale VM, Chatterjee P, Chakraborty S (2012) Decision making for facility location selection using PROMETHEE II method. International Journal of Industrial and Systems Engineering 1, 11(1-2): 16-30.
  • Başer KHC (2000) Sustainable wild harvesting of medicinal and aromatic plants: an educational approach, harvesting on non-wood forest products. In Seminar Proceedings, Menemen-İzmir, Turkey.
  • Bayram E, Kırıcı S, Tansı S, Yılmaz G, Kızıl OAS, Telci İ (2010) Tıbbi ve aromatik bitkiler üretiminin arttırılması olanakları. TMMOB Ziraat Mühendisleri Odası, Ziraat Mühendisliği VII. Teknik Kongresi, 11, 15.
  • Cakmak E, Guney E (2023) Spare parts inventory classification using Neutrosophic Fuzzy EDAS method in the aviation industry. Expert Systems with Applications, 224: 120008.
  • Chen SJ, Hwang CI (1992) Fuzzy multiple attribute decision making: methods and applications. Berlin Heidelberg: Springer.
  • Chowdhury P, Paul SK (2020) Applications of MCDM methods in research on corporate sustainability: a systematic literature review. Management of Environmental Quality: An International Journal.
  • Christenhusz MJ, Byng JW (2016) The number of known plants species in the world and its annual increase. Phytotaxa, 261(3): 201-217.
  • Çebi F, Otay İ (2015) Multi-criteria and multi-stage facility location selection under interval type-2 fuzzy environment: a case study for a cement factory. International Journal of Computational İntelligence Systems, 8(2): 330-344.
  • Drezner Z, Hamacher HW (Eds.) (2004) Facility location: applications and theory. Springer Science Business Media.
  • Dumrul C, Bilgili F, Zarali F, Dumrul Y, Kiliçarslan Z (2024) The evaluation of renewable energy alternatives in Turkey using intuitionistic-fuzzy EDAS methodology. Environmental Science and Pollution Research, 31(10): 15503-15524.
  • Emovon I, Oghenenyerovwho OS (2020) Application of MCDM method in material selection for optimal design: a review. Results in Materials, 7: 100115.
  • Ertuğrul İ, Karakaşoğlu N (2008) Comparison of fuzzy AHP and fuzzy TOPSIS methods for facility location selection. The International Journal of Advanced Manufacturing Technology, 39: 783-795.
  • Farahani RZ, SteadieSeifi M, Asgari N (2010) Multiple criteria facility location problems: a survey. Applied Mathematical Modelling, 34(7): 1689-1709.
  • Garg H, Sharaf IM (2022) A new spherical aggregation function with the concept of spherical fuzzy difference for spherical fuzzy EDAS and its application to industrial robot selection. Computational and Applied Mathematics, 41(5): 212.
  • Gul M, Guneri AF (2021) Hospital location selection: a systematic literature review on methodologies and applications. Mathematical Problems in Engineering, 2021: 1-14.
  • Güner A, Aslan S (Eds.) (2012) Türkiye bitkileri listesi:(damarlı bitkiler) Nezahat Gökyiǧit Botanik Bahçesi Yayınları.
  • Halil Ş, Demiral MF (2016) Hospital location selection with grey system theory. International Advisory Board, 23: 373.
  • Heizer J, Render B, Munson C (2008) Operations management. Prentice-Hall.
  • IUCN Species Survival Commission Medicinal Plant Specialist Group (2007) “Why Conserve and Manage Medicinal Plants?” Web resource: www.iucn.org/themes/ssc/sgs/mpsg/main/Why.html.
  • Kahraman C, Keshavarz Ghorabaee M, Zavadskas EK, Cevik Onar S, Yazdani M, Oztaysi B (2017) Intuitionistic fuzzy EDAS method: an application to solid waste disposal site selection. Journal of Environmental Engineering and Landscape Management, 25(1): 1-12.
  • Keesstra SD, Bouma J, Wallinga J, Tittonell P, Smith P, Cerdà A, Fresco, LO (2016) The significance of soils and soil science towards realization of the United Nations Sustainable Development Goals. Soil.
  • Kengpol A, Rontlaong P, Tuominen M (2013) A decision support system for selection of solar power plant locations by applying fuzzy AHP and TOPSIS: An empirical study.
  • Keshavarz Ghorabaee MK, Zavadskas EK, Amiri M, Turskis Z (2016) Extended EDAS Method for Fuzzy Multicriteria Decision-making: an application to supplier selection. International Journal of Computers Communications & Control, 11(3): 358–371.
  • Keshavarz Ghorabaee MK, Zavadskas EK, Olfat L, Turskis Z (2015) Multi-criteria ınventory classification using a new method of evaluation based on distance from average solution (EDAS). Informatica, 26(3): 435–451.
  • Kheybari S, Kazemi M, Rezaei J (2019) Bioethanol facility location selection using best-worst method. Applied energy, 242: 612-623.
  • Khorshidi M, Erkayman B, Albayrak Ö, Kılıç R, Demir Hİ (2022) Solar power plant location selection using integrated fuzzy DEMATEL and fuzzy MOORA method. International Journal of Ambient Energy, 43(1): 7400-7409.
  • Ko JS (2005) Solving a distribution facility location problem using an analytic hierarchy process approach. ISAHP Proceedings Honolulu Hawaii: 1991-1996.
  • Lubbe A, Verpoorte R (2011) Cultivation of medicinal and aromatic plants for specialty industrial materials. Industrial Crops and Products, 34: 785–801.
  • MacCarthy BL, Atthirawong W (2003) Factors affecting location decisions in international operations–a Delphi study. International Journal of Operations Production Management, 23(7): 794-818.
  • Marinelli J (Ed.) (2005) Plant: the ultimate visual reference to plants and flowers of the world. New York: DK Publishing, Inc.
  • Menekşe A, Camgöz Akdağ H (2022) Distance education tool selection using novel spherical fuzzy AHP EDAS. Soft Computing, 26(4): 1617-1635.
  • Menekşe A, Ertemel AV, Camgoz Akdag H, Gorener A (2023) Additive manufacturing process selection for automotive industry using Pythagorean fuzzy CRITIC EDAS. Plos One, 18(3): e0282676.
  • Nhi THT, Wang CN, Van Thanh N (2022) Fuzzy multi-criteria decision making for solar power plant location selection. Computers, Materials Continua, 72(3): 4853-4865.
  • Olcer AY, Odabasi AY (2005) A new fuzzy multiple attributive group decision making methodology and its application to propulsion/manoeuvring system selection problem. European Journal of Operational Research, 166(1): 93–114.
  • Owen SH, Daskin MS (1998) Strategic facility location: a review. European Journal of Operational Research, 111(3): 423-447.
  • Özkan B, Erdem M, Özceylan E (2022) Evaluation of Asian countries using data center security index: a spherical fuzzy AHP-based EDAS approach. Computers & Security, 122: 102900.
  • Paul TK, Jana C, Pal M (2023) Multi-criteria group decision-making method in disposal of municipal solid waste based on cubic Pythagorean fuzzy EDAS approach with incomplete weight information. Applied Soft Computing, 144: 110515.
  • Polat G, Bayhan HG (2022) Selection of HVAC-AHU system supplier with environmental considerations using Fuzzy EDAS method. International Journal of Construction Management, 22(10): 1863-1871.
  • Rahman MS, Ali MI, Hossain U, Mondal TK (2018) Facility location selection for plastic manufacturing industry in Bangladesh by using AHP method. International Journal of Research in Industrial Engineering, 7(3): 307-319.
  • Renganath K, Suresh M (2016) Supplier selection using fuzzy MCDM techniques: A literature review. In 2016 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), IEEE, pp: 1-6.
  • Samastı M, Türkan YS, Güler M, Ciner MN, Namlı E (2024) Site selection of medical waste disposal facilities using the interval-valued neutrosophic fuzzy EDAS Method: the case study of Istanbul. Sustainability, 16(7): 2881.
  • Siksnelyte-Butkiene I, Zavadskas EK, Streimikiene D (2020) Multi-criteria decision-making (MCDM) for the assessment of renewable energy technologies in a household: a review. Energies, 13(5): 1164.
  • Silva S, Alçada-Almeida L, Dias LC (2014) Biogas plants site selection integrating multicriteria decision aid methods and GIS techniques: a case study in a Portuguese region. Biomass and Bioenergy, 71: 58-68.
  • Stević Ž, Vasiljevic M, Zavadskas EK, Sremac S, Turskis Z (2018) Selection of carpenter manufacturer using fuzzy EDAS method.
  • Suman MNH, Sarfaraj N, Chyon FA, Fahim MRI (2021) Facility location selection for the furniture industry of Bangladesh: Comparative AHP and FAHP analysis. International Journal of Engineering Business Management, 13: 18479790211030851.
  • URL-1:https://bacem.com.tr/sayfa/distilasyon-unitesi-bolumu
  • URL-2:https://guneysinir.bel.tr/haberler/guneysinir-tibbi-aromatik-bitkiler-distilasyon-merkezi-acildi.html
  • URL-3:https://mushrooms.caliskantarim.com/tr/mushrooms/about.html
  • URL-4:https://www.mugla.bel.tr/haber/buyuksehirden-tibbi-aromatik-bitki-ureticilerine-distilasyon-hizmeti
  • URL-5:https://www.samsungazetesi.com/samsunda-tibbi-ve-aromatik-bitkiler-icin-kurutma-tesisi-kuruldu
  • URL-6: https://www.sekapark.com.tr/sayfa/Tesislerimiz
  • URL-7: https://www.uludagagro.com/
  • URL-8: https://tibbiaromatik.artvin.edu.tr/genel-bilgiler-108
  • Vahdani B, Mousavi SM, Tavakkoli-Moghaddam R (2013) Plant location selection by using a three-step methodology: Delphi-AHP-VIKOR. International Journal of Industrial and Manufacturing Engineering, 7(6): 1289-1292.
  • Vahidnia MH, Alesheikh AA, Alimohammadi A (2009) Hospital site selection using fuzzy AHP and its derivatives. Journal of Environmental Management, 90(10): 3048-3056.
  • Wang YJ, Lee HS (2007) Generalizing TOPSIS for fuzzy multiple-criteria group decision making. Computers & Mathematics with Applications, 53(11): 1762–1772.
  • Xidonas P, Psarras J (2009) Equity portfolio management within the MCDM frame: a literature review. International Journal of Banking, Accounting and Finance, 1(3): 285-309.
  • Yang J, Lee H (1997) An AHP decision model for facility location selection. Facilities, 15(9/10): 241-254.
  • Yaşlıoğlu MM, Önder E (2016) Solving facility location problem for a plastic goods manufacturing company in Turkey using AHP and TOPSIS methods. Yönetim Bilimleri Dergisi.
  • Yong D (2006) Plant location selection based on fuzzy TOPSIS. The International Journal of Advanced Manufacturing Technology, 28: 839-844.
  • Zadeh LA (1965) Fuzzy sets. Information and Control, 8(3): 338–353. Zavadskas EK, Turskis Z (2011) Multiple criteria decision making (MCDM) methods in economics: an overview. Technological and Economic Development of Economy, 17(2): 397-427.
  • Zimmermann HJ (2010) Fuzzy set theory. Wiley Interdisciplinary Reviews: Computational Statistics, 2(3): 317–332.

Bulanık EDAS yöntemi ile tıbbi aromatik bitki işleme tesisi yer seçimi: Artvin örneği

Year 2024, Volume: 25 Issue: 1, 136 - 150, 15.05.2024
https://doi.org/10.17474/artvinofd.1453305

Abstract

İklim değişikliği, biyoçeşitlilik ve toprağın iyi yönetilmesi dünyadaki hızlı nüfus artışı ile birlikte kıt olan bu tür kaynakların daha iyi yönetilmesi ve verimli kullanılması gerekliliğinin önemini artırmaktadır. Tıbbı ve aromatik bitkiler de (TAB) bu kaynaklar arasında yer almakta ve ekonomik açıdan da bir katma değer potansiyeli bulunmaktadır. Doğadan doğrudan veya kültür yolu ile üretimi gerçekleştirilen TAB’ların işlenmesi için tesis yeri seçimi önemli bir stratejik karar unsuru olmaktadır ve genel olarak tesis yeri seçimi problemi, işletmelerin veya örgütlerin karşılaştığı en temel stratejik karar verme problemlerinden biri olarak ortaya çıkmaktadır. Çok fazla faktörün minör veya majör etkilerinin bulunduğu bu karmaşık karar verme sürecini çözümlemek için bu çalışmada çok kriterli karar verme yöntemlerinden (ÇKKV) biri olan EDAS (The evaluation based on distance from average solution) metodolojisinin adımları izlenmiştir. Bunun yanı sıra bulanık teorinin belirsizlik ve eksik bilgi ile baş edebilme yeteneğinden faydalanarak (trapezoidal fuzzy numbers – yamuk bulanık sayılar) problemin çözümüne ulaşmada zaman ve kaynak tasarrufu olarak önemli bir avantaj elde edilmiştir. Çözüm sürecinde üç karar verici ve altı alternatif lokasyonu dilsel terimlerle değerlendirerek bir öncelik sıralaması oluşturulmuş ve en uygun konum (A2- Seyitler Yerleşkesi) belirlenmiştir.

References

  • Akram M, Ramzan N, Deveci M (2023) Linguistic pythagorean fuzzy CRITIC-EDAS method for multiple-attribute group decision analysis. Engineering Applications of Artificial Intelligence, 119: 105777.
  • Almutairi K (2022) Determining the appropriate location for renewable hydrogen development using multi‐criteria decision‐making approaches. International Journal of Energy Research, 46(5): 5876-5895.
  • Athawale VM, Chatterjee P, Chakraborty S (2012) Decision making for facility location selection using PROMETHEE II method. International Journal of Industrial and Systems Engineering 1, 11(1-2): 16-30.
  • Başer KHC (2000) Sustainable wild harvesting of medicinal and aromatic plants: an educational approach, harvesting on non-wood forest products. In Seminar Proceedings, Menemen-İzmir, Turkey.
  • Bayram E, Kırıcı S, Tansı S, Yılmaz G, Kızıl OAS, Telci İ (2010) Tıbbi ve aromatik bitkiler üretiminin arttırılması olanakları. TMMOB Ziraat Mühendisleri Odası, Ziraat Mühendisliği VII. Teknik Kongresi, 11, 15.
  • Cakmak E, Guney E (2023) Spare parts inventory classification using Neutrosophic Fuzzy EDAS method in the aviation industry. Expert Systems with Applications, 224: 120008.
  • Chen SJ, Hwang CI (1992) Fuzzy multiple attribute decision making: methods and applications. Berlin Heidelberg: Springer.
  • Chowdhury P, Paul SK (2020) Applications of MCDM methods in research on corporate sustainability: a systematic literature review. Management of Environmental Quality: An International Journal.
  • Christenhusz MJ, Byng JW (2016) The number of known plants species in the world and its annual increase. Phytotaxa, 261(3): 201-217.
  • Çebi F, Otay İ (2015) Multi-criteria and multi-stage facility location selection under interval type-2 fuzzy environment: a case study for a cement factory. International Journal of Computational İntelligence Systems, 8(2): 330-344.
  • Drezner Z, Hamacher HW (Eds.) (2004) Facility location: applications and theory. Springer Science Business Media.
  • Dumrul C, Bilgili F, Zarali F, Dumrul Y, Kiliçarslan Z (2024) The evaluation of renewable energy alternatives in Turkey using intuitionistic-fuzzy EDAS methodology. Environmental Science and Pollution Research, 31(10): 15503-15524.
  • Emovon I, Oghenenyerovwho OS (2020) Application of MCDM method in material selection for optimal design: a review. Results in Materials, 7: 100115.
  • Ertuğrul İ, Karakaşoğlu N (2008) Comparison of fuzzy AHP and fuzzy TOPSIS methods for facility location selection. The International Journal of Advanced Manufacturing Technology, 39: 783-795.
  • Farahani RZ, SteadieSeifi M, Asgari N (2010) Multiple criteria facility location problems: a survey. Applied Mathematical Modelling, 34(7): 1689-1709.
  • Garg H, Sharaf IM (2022) A new spherical aggregation function with the concept of spherical fuzzy difference for spherical fuzzy EDAS and its application to industrial robot selection. Computational and Applied Mathematics, 41(5): 212.
  • Gul M, Guneri AF (2021) Hospital location selection: a systematic literature review on methodologies and applications. Mathematical Problems in Engineering, 2021: 1-14.
  • Güner A, Aslan S (Eds.) (2012) Türkiye bitkileri listesi:(damarlı bitkiler) Nezahat Gökyiǧit Botanik Bahçesi Yayınları.
  • Halil Ş, Demiral MF (2016) Hospital location selection with grey system theory. International Advisory Board, 23: 373.
  • Heizer J, Render B, Munson C (2008) Operations management. Prentice-Hall.
  • IUCN Species Survival Commission Medicinal Plant Specialist Group (2007) “Why Conserve and Manage Medicinal Plants?” Web resource: www.iucn.org/themes/ssc/sgs/mpsg/main/Why.html.
  • Kahraman C, Keshavarz Ghorabaee M, Zavadskas EK, Cevik Onar S, Yazdani M, Oztaysi B (2017) Intuitionistic fuzzy EDAS method: an application to solid waste disposal site selection. Journal of Environmental Engineering and Landscape Management, 25(1): 1-12.
  • Keesstra SD, Bouma J, Wallinga J, Tittonell P, Smith P, Cerdà A, Fresco, LO (2016) The significance of soils and soil science towards realization of the United Nations Sustainable Development Goals. Soil.
  • Kengpol A, Rontlaong P, Tuominen M (2013) A decision support system for selection of solar power plant locations by applying fuzzy AHP and TOPSIS: An empirical study.
  • Keshavarz Ghorabaee MK, Zavadskas EK, Amiri M, Turskis Z (2016) Extended EDAS Method for Fuzzy Multicriteria Decision-making: an application to supplier selection. International Journal of Computers Communications & Control, 11(3): 358–371.
  • Keshavarz Ghorabaee MK, Zavadskas EK, Olfat L, Turskis Z (2015) Multi-criteria ınventory classification using a new method of evaluation based on distance from average solution (EDAS). Informatica, 26(3): 435–451.
  • Kheybari S, Kazemi M, Rezaei J (2019) Bioethanol facility location selection using best-worst method. Applied energy, 242: 612-623.
  • Khorshidi M, Erkayman B, Albayrak Ö, Kılıç R, Demir Hİ (2022) Solar power plant location selection using integrated fuzzy DEMATEL and fuzzy MOORA method. International Journal of Ambient Energy, 43(1): 7400-7409.
  • Ko JS (2005) Solving a distribution facility location problem using an analytic hierarchy process approach. ISAHP Proceedings Honolulu Hawaii: 1991-1996.
  • Lubbe A, Verpoorte R (2011) Cultivation of medicinal and aromatic plants for specialty industrial materials. Industrial Crops and Products, 34: 785–801.
  • MacCarthy BL, Atthirawong W (2003) Factors affecting location decisions in international operations–a Delphi study. International Journal of Operations Production Management, 23(7): 794-818.
  • Marinelli J (Ed.) (2005) Plant: the ultimate visual reference to plants and flowers of the world. New York: DK Publishing, Inc.
  • Menekşe A, Camgöz Akdağ H (2022) Distance education tool selection using novel spherical fuzzy AHP EDAS. Soft Computing, 26(4): 1617-1635.
  • Menekşe A, Ertemel AV, Camgoz Akdag H, Gorener A (2023) Additive manufacturing process selection for automotive industry using Pythagorean fuzzy CRITIC EDAS. Plos One, 18(3): e0282676.
  • Nhi THT, Wang CN, Van Thanh N (2022) Fuzzy multi-criteria decision making for solar power plant location selection. Computers, Materials Continua, 72(3): 4853-4865.
  • Olcer AY, Odabasi AY (2005) A new fuzzy multiple attributive group decision making methodology and its application to propulsion/manoeuvring system selection problem. European Journal of Operational Research, 166(1): 93–114.
  • Owen SH, Daskin MS (1998) Strategic facility location: a review. European Journal of Operational Research, 111(3): 423-447.
  • Özkan B, Erdem M, Özceylan E (2022) Evaluation of Asian countries using data center security index: a spherical fuzzy AHP-based EDAS approach. Computers & Security, 122: 102900.
  • Paul TK, Jana C, Pal M (2023) Multi-criteria group decision-making method in disposal of municipal solid waste based on cubic Pythagorean fuzzy EDAS approach with incomplete weight information. Applied Soft Computing, 144: 110515.
  • Polat G, Bayhan HG (2022) Selection of HVAC-AHU system supplier with environmental considerations using Fuzzy EDAS method. International Journal of Construction Management, 22(10): 1863-1871.
  • Rahman MS, Ali MI, Hossain U, Mondal TK (2018) Facility location selection for plastic manufacturing industry in Bangladesh by using AHP method. International Journal of Research in Industrial Engineering, 7(3): 307-319.
  • Renganath K, Suresh M (2016) Supplier selection using fuzzy MCDM techniques: A literature review. In 2016 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), IEEE, pp: 1-6.
  • Samastı M, Türkan YS, Güler M, Ciner MN, Namlı E (2024) Site selection of medical waste disposal facilities using the interval-valued neutrosophic fuzzy EDAS Method: the case study of Istanbul. Sustainability, 16(7): 2881.
  • Siksnelyte-Butkiene I, Zavadskas EK, Streimikiene D (2020) Multi-criteria decision-making (MCDM) for the assessment of renewable energy technologies in a household: a review. Energies, 13(5): 1164.
  • Silva S, Alçada-Almeida L, Dias LC (2014) Biogas plants site selection integrating multicriteria decision aid methods and GIS techniques: a case study in a Portuguese region. Biomass and Bioenergy, 71: 58-68.
  • Stević Ž, Vasiljevic M, Zavadskas EK, Sremac S, Turskis Z (2018) Selection of carpenter manufacturer using fuzzy EDAS method.
  • Suman MNH, Sarfaraj N, Chyon FA, Fahim MRI (2021) Facility location selection for the furniture industry of Bangladesh: Comparative AHP and FAHP analysis. International Journal of Engineering Business Management, 13: 18479790211030851.
  • URL-1:https://bacem.com.tr/sayfa/distilasyon-unitesi-bolumu
  • URL-2:https://guneysinir.bel.tr/haberler/guneysinir-tibbi-aromatik-bitkiler-distilasyon-merkezi-acildi.html
  • URL-3:https://mushrooms.caliskantarim.com/tr/mushrooms/about.html
  • URL-4:https://www.mugla.bel.tr/haber/buyuksehirden-tibbi-aromatik-bitki-ureticilerine-distilasyon-hizmeti
  • URL-5:https://www.samsungazetesi.com/samsunda-tibbi-ve-aromatik-bitkiler-icin-kurutma-tesisi-kuruldu
  • URL-6: https://www.sekapark.com.tr/sayfa/Tesislerimiz
  • URL-7: https://www.uludagagro.com/
  • URL-8: https://tibbiaromatik.artvin.edu.tr/genel-bilgiler-108
  • Vahdani B, Mousavi SM, Tavakkoli-Moghaddam R (2013) Plant location selection by using a three-step methodology: Delphi-AHP-VIKOR. International Journal of Industrial and Manufacturing Engineering, 7(6): 1289-1292.
  • Vahidnia MH, Alesheikh AA, Alimohammadi A (2009) Hospital site selection using fuzzy AHP and its derivatives. Journal of Environmental Management, 90(10): 3048-3056.
  • Wang YJ, Lee HS (2007) Generalizing TOPSIS for fuzzy multiple-criteria group decision making. Computers & Mathematics with Applications, 53(11): 1762–1772.
  • Xidonas P, Psarras J (2009) Equity portfolio management within the MCDM frame: a literature review. International Journal of Banking, Accounting and Finance, 1(3): 285-309.
  • Yang J, Lee H (1997) An AHP decision model for facility location selection. Facilities, 15(9/10): 241-254.
  • Yaşlıoğlu MM, Önder E (2016) Solving facility location problem for a plastic goods manufacturing company in Turkey using AHP and TOPSIS methods. Yönetim Bilimleri Dergisi.
  • Yong D (2006) Plant location selection based on fuzzy TOPSIS. The International Journal of Advanced Manufacturing Technology, 28: 839-844.
  • Zadeh LA (1965) Fuzzy sets. Information and Control, 8(3): 338–353. Zavadskas EK, Turskis Z (2011) Multiple criteria decision making (MCDM) methods in economics: an overview. Technological and Economic Development of Economy, 17(2): 397-427.
  • Zimmermann HJ (2010) Fuzzy set theory. Wiley Interdisciplinary Reviews: Computational Statistics, 2(3): 317–332.
There are 64 citations in total.

Details

Primary Language Turkish
Subjects Forestry Sciences (Other)
Journal Section Research Article
Authors

Enis Küçük 0000-0003-2070-3881

Ertan Dinç 0000-0002-0345-7781

Tayfun Öztürk 0000-0002-0252-2780

Publication Date May 15, 2024
Submission Date March 15, 2024
Acceptance Date April 22, 2024
Published in Issue Year 2024Volume: 25 Issue: 1

Cite

APA Küçük, E., Dinç, E., & Öztürk, T. (2024). Bulanık EDAS yöntemi ile tıbbi aromatik bitki işleme tesisi yer seçimi: Artvin örneği. Artvin Çoruh Üniversitesi Orman Fakültesi Dergisi, 25(1), 136-150. https://doi.org/10.17474/artvinofd.1453305
AMA Küçük E, Dinç E, Öztürk T. Bulanık EDAS yöntemi ile tıbbi aromatik bitki işleme tesisi yer seçimi: Artvin örneği. ACUJFF. May 2024;25(1):136-150. doi:10.17474/artvinofd.1453305
Chicago Küçük, Enis, Ertan Dinç, and Tayfun Öztürk. “Bulanık EDAS yöntemi Ile tıbbi Aromatik Bitki işleme Tesisi Yer seçimi: Artvin örneği”. Artvin Çoruh Üniversitesi Orman Fakültesi Dergisi 25, no. 1 (May 2024): 136-50. https://doi.org/10.17474/artvinofd.1453305.
EndNote Küçük E, Dinç E, Öztürk T (May 1, 2024) Bulanık EDAS yöntemi ile tıbbi aromatik bitki işleme tesisi yer seçimi: Artvin örneği. Artvin Çoruh Üniversitesi Orman Fakültesi Dergisi 25 1 136–150.
IEEE E. Küçük, E. Dinç, and T. Öztürk, “Bulanık EDAS yöntemi ile tıbbi aromatik bitki işleme tesisi yer seçimi: Artvin örneği”, ACUJFF, vol. 25, no. 1, pp. 136–150, 2024, doi: 10.17474/artvinofd.1453305.
ISNAD Küçük, Enis et al. “Bulanık EDAS yöntemi Ile tıbbi Aromatik Bitki işleme Tesisi Yer seçimi: Artvin örneği”. Artvin Çoruh Üniversitesi Orman Fakültesi Dergisi 25/1 (May 2024), 136-150. https://doi.org/10.17474/artvinofd.1453305.
JAMA Küçük E, Dinç E, Öztürk T. Bulanık EDAS yöntemi ile tıbbi aromatik bitki işleme tesisi yer seçimi: Artvin örneği. ACUJFF. 2024;25:136–150.
MLA Küçük, Enis et al. “Bulanık EDAS yöntemi Ile tıbbi Aromatik Bitki işleme Tesisi Yer seçimi: Artvin örneği”. Artvin Çoruh Üniversitesi Orman Fakültesi Dergisi, vol. 25, no. 1, 2024, pp. 136-50, doi:10.17474/artvinofd.1453305.
Vancouver Küçük E, Dinç E, Öztürk T. Bulanık EDAS yöntemi ile tıbbi aromatik bitki işleme tesisi yer seçimi: Artvin örneği. ACUJFF. 2024;25(1):136-50.
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