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An Integrated HFLTS and HF-TOPSIS Approach for Wind Turbine Site Selection Problem

Yıl 2025, Cilt: 14 Sayı: 2, 930 - 951, 30.06.2025

Koksal Aktas , Ahmet Aktas , Mehmet Kabak

https://doi.org/10.17798/bitlisfen.1621902

Öz

A vast majority of decision problems consist of conflicting criteria and non-dominating alternatives. To solve such kinds of decision problems, multiple criteria decision-making (MCDM) techniques have widely been used in many fields, so far. Moreover, hybrid decision-making approaches are also developed by the integration of different MCDM techniques in order to utilize the benefits of those methods. The main aim in this study is to introduce an integrated decision-making method for decision problems under uncertainty. Within this approach, Hesitant Fuzzy Linguistic Term Sets (HFLTS) and Hesitant Fuzzy Technique for Order Preference by Similarity to Ideal Solution (HF-TOPSIS) are integrated. The HFLTS method is used for the determination of criteria weights and decision alternatives are evaluated by using the HF-TOPSIS technique. The applicability of the method is demonstrated on an application of the wind turbine location problem.

Anahtar Kelimeler

Hesitant fuzzy sets HFLTS TOPSIS site selection wind energy.

Etik Beyan

The study is complied with research and publication ethics.

Kaynakça

  • G.S. de Assis, M. dos Santos, and M. P. Basilio, M.P. “Use of the WASPAS Method to Select Suitable Helicopters for Aerial Activity Carried Out by the Military Police of the State of Rio de Janeiro,” Axioms, vol. 12, 77. 2023.
  • S. Iskanderani, O. Bafail, and M. Alamoudi, “Optimizing Sugar Manufacturing: A Hybrid Simulation-Based Approach and MCDM for Efficient Decision Making,” Axioms, 12, 975, 2023.
  • N. V. Thanh, N. T. K. Lan, “A New Hybrid Triple Bottom Line Metrics and Fuzzy MCDM Model: Sustainable Supplier Selection in the Food-Processing Industry,” Axioms, vol. 11, 57, 2022.
  • H.-T. Le, T.-C. Chu, “Ranking Alternatives Using a Fuzzy Preference Relation-Based Fuzzy VIKOR Method,” Axioms, vol. 12, 1079, 2023.
  • H. A. Es, C. Hamzacebi, and S. U. O. Firat, “GRA-TRI: A Multicriteria Decision Aid Classification Method based on Grey Relational Analysis,” J. Grey Syst., vol. 30, pp. 1–12, 2018.
  • M. Çolak, İ. Kaya, “Prioritization of Renewable Energy Alternatives by Using an Integrated Fuzzy MCDM Model: A Real Case Application for Turkey,” Renew. Sustain. Energy Rev., vol. 80, pp. 840–853, 2017.
  • T.-C. Chu, T. B. H. Nghiem, “Extension of Fuzzy ELECTRE I for Evaluating Demand Forecasting Methods in Sustainable Manufacturing,” Axioms, vol. 12, 926, 2023.
  • A. Łuczak, M. A. Just, “Complex MCDM Procedure for the Assessment of Economic Development of Units at Different Government Levels,” Mathematics, vol. 8, 1067, 2020.
  • T. L. Saaty, What is the analytic hierarchy process? In Mathematical Models for Decision Support; Berlin/Heidelberg: Springer, 1988; pp. 109–121.
  • T. L. Saaty, L. G. Vargas. 2006. Decision Making with the Analytic Network Process. Berlin/Heidelberg: Springer, vol. 282.
  • İ. Gölcük, A. Baykasoglu, “An analysis of DEMATEL approaches for criteria interaction handling within ANP,” Expert Syst. Appl., vol. 46, pp. 346–366, 2016.
  • B. Efe, M. A. Yerlikaya, and Ö. F. Efe, “Mobile phone selection based on a novel quality function deployment approach,” Soft Comput., vol. 24, pp. 15447–15461, 2020.
  • A. Yildizbasi, Y. Arioz, “Green supplier selection in new era for sustainability: A novel method for integrating big data analytics and a hybrid fuzzy multi-criteria decision making,” Soft Comput., vol. 26, pp. 253–270, 2022.
  • C. Çetinkaya, M. Kabak, M. Erbaş, and E. Özceylan, “Evaluation of ecotourism sites: A GIS-based multi-criteria decision analysis,” Kybernetes, vol. 47, pp. 1664–1686, 2018.
  • G. Ozkaya, A. Demirhan, “Analysis of Countries in Terms of Artificial Intelligence Technologies: PROMETHEE and GAIA Method Approach,” Sustainability, 15, 4604, 2023.
  • I. Clímaco, C. Henggeler Antunes, “Evaluation of Fiscal and Non-Fiscal Policies for Electric Vehicles—A Multi-Criterion Sorting Approach,” Sustainability, vol. 15, 6213, 2023.
  • T. B. H. Nghiem, T.-C. Chu, “Evaluating Lean Facility Layout Designs Using a BWM-Based Fuzzy ELECTRE I Method,” Axioms, vol. 11, 447, 2022.
  • A. Karasan, F. K. Gündoǧdu, and S. Aydın, “Decision-making methodology by using multi-expert knowledge for uncertain environments: Green metric assessment of universities,” Environ. Dev. Sustain., vol. 25, pp. 7393–7422, 2022.
  • M. A. Yerlikaya, K. Yildiz, and B. N. Keskin, “Solution proposal for completed preference structure in ORESTE method,” Sci Rep, vol. 13, 4754, 2023.
  • S. Aydin, “A Novel Multi-Expert Mabac Method Based on Fermatean Fuzzy Sets,” J. Mult. Valued Log. Soft Comput., vol. 37, pp. 533–552, 2021.
  • G. Özçelik, M. Nalkıran, “An extension of EDAS method equipped with trapezoidal bipolar fuzzy information: An application from healthcare system,” Int. J. Fuzzy Syst., vol. 23, pp. 2348–2366, 2021.
  • S. Gáspár, Z. Musinszki, I. Z. Hágen, Á. Barta, J. Bárczi, and G. Thalmeiner, “Developing a Controlling Model for Analyzing the Subjectivity of Enterprise Sustainability and Expert Group Judgments Using Fuzzy Triangular Membership Functions,” Sustainability, vol. 15, 7981, 2023.
  • K. R. Hindi, A. El-Assal, I. Sabry, “Multi-criteria decision making methods comparative analysis in Fuzzy Environment: article review,” Benha J. Appl. Sci., vol. 7, pp. 227-235, 2022.
  • V. Torra, “Hesitant fuzzy sets,” Int. J. Intell. Syst., vol. 25, pp. 529–539, 2010.
  • M. Yavuz, B. Oztaysi, S. C. Onar, and C. Kahraman, “Multi-criteria evaluation of alternative-fuel vehicles via a hierarchical hesitant fuzzy linguistic model,” Expert Syst. Appl., vol. 42, pp. 2835–2848, 2015.
  • Z. Xu, X. Zhang, “Hesitant fuzzy multi-attribute decision making based on TOPSIS with incomplete weight information,” Knowl.- Based Syst., vol. 52, pp. 53–64, 2013.
  • E. K. Zavadskas, Z. Turskis, “Multiple criteria decision making (MCDM) methods in economics: An overview,” Technol. Econ. Dev. Econ., vol. 17, pp. 397–427, 2011.
  • S.-H. Tsaur, T.-Y. Chang, and C. H. Yen, “The evaluation of airline service quality by fuzzy MCDM,” Tour. Manag. vol. 23, pp. 107–115, 2002.
  • B. D. Rouyendegh, ”The intuitionistic fuzzy ELECTRE model,” Int. J. Manag. Sci. Eng. Manag. vol. 13, pp. 139–145, 2018.
  • A. Pınar, R. Babak Daneshvar, and Y. S. Özdemir, “q-Rung Orthopair Fuzzy TOPSIS Method for Green Supplier Selection Problem,” Sustainability, vol. 13, 985, 2021.
  • K. Zahid, M. Akram, and C. Kahraman, “A new ELECTRE-based method for group decision-making with complex spherical fuzzy information,” Knowl. Based Syst. vol. 243, 108525, 2022.
  • A. V. Ertemel, A. Menekse, and H. Camgoz Akdag, “Smartphone Addiction Assessment Using Pythagorean Fuzzy CRITIC-TOPSIS,” Sustainability, vol. 15, 3955, 2023.
  • S. Cebi, F. Kutlu Gündoğdu, and C. Kahraman, “Consideration of reciprocal judgments through Decomposed Fuzzy Analytical Hierarchy Process: A case study in the pharmaceutical industry,” Appl. Soft Comput., vol. 134, 110000, 2023.
  • A. Aktas, B. Ecer, and M. Kabak, “A Hybrid Hesitant Fuzzy Model for Healthcare Systems Ranking of European Countries,” Systems, vol. 10, 219, 2022.
  • R. M. Rodriguez, L. Martinez, L. and F. Herrera, “Hesitant fuzzy linguistic term sets for decision making,” IEEE Trans. Fuzzy Syst., vol. 20, pp. 109–119, 2012.
  • C. L. Hwang, K. Yoon, Multiple Attribute Decision Making: Methods and Applications, A State of the Art Survey; New York, NY: Springer, 1981.
  • Z. Xu, M. Xia, “On Distance and Correlation Measures of Hesitant Fuzzy Information,” Int. J. Intell. Syst, vol. 26, pp. 410–425, 2011.
  • J. Dong, T.-T. Feng, Y.-S. Yang, and Y. Ma, “Macro-site selection of wind/solar hybrid power station based on ELECTRE-II,” Renew. Sustain. Energy Rev., vol. 35, pp. 194–204, 2014.
  • N. C. Chatterjee, G. K. Bose, “A COPRAS-F base multi-criteria group decision making approach for site selection of wind farm,” Decis. Sci. Lett., vol. 2, pp. 1–10, 2013.
  • T. Kaya, C. Kahraman, “Multicriteria renewable energy planning using an integrated fuzzy VIKOR & AHP methodology: The case of Istanbul”, Energy, vol. 35, pp. 2517–2527, 2010.
  • I. Talinli, E. Topuz, E. Aydin, and S. B. Kabakcı, “A Holistic Approach for Wind Farm Site Selection by FAHP”, IntechOpen. Available online: https://www.researchgate.net/publication/221912736_A_Holistic_Approach_for_Wind_Farm_Site_Selection_by_Using_FAHP
  • S. Cebi, C. Kahraman, “Using Multi Attribute Choquet Integral in Site Selection of Wind Energy Plants: The Case of Turkey,” J. Mult. Valued Log. Soft Comput., vol. 20, 423–443, 2013.
  • M.S. Kang, C.S. Chen, Y.L. Ke, A.H. Lee, T.T. Ku, and H.Y. Kang, “Applications of FANP and BOCR in renewable energy-study on the choice of the sites for wind farms,” IEEE Trans. Ind. Appl., vol. 49, pp. 982–989, 2013.
  • W. Yun-Na, Y. Yi-Sheng, F. Tian-Tian, K. Li-Na, L. Wei, and F. Luo-Jie, “Macro-site selection of wind/solar hybrid power sta-tion based on Ideal Matter-Element Model,” Int. J. Electr. Power Energy Syst., vol. 50, pp. 76–84, 2013.
  • R. Van Haaren, V. Fthenakis, “GIS-based wind farm site selection using spatial multi-criteria analysis (SMCA): Evaluating the case for New York State,” Renew. Sustain. Energy Rev., vol. 15, pp. 3332–3340, 2011.
  • R. H. A. Hamid, “A GIS-DSS for wind farms industry in Egypt,” 2011 International Conference & Utility Exhibition on Power and Energy Systems: Issues and Prospects for Asia (ICUE), Pattaya, Thailand, 28-30 September 2011.
  • L. Selcuk, “An avalanche hazard model for Bitlis Province, Turkey, using GIS based multicriteria decision analysis,” Turk. J. Earth Sci., vol. 22, pp. 523–535, 2013.
  • M. Kabak, H. Javadi, A. Aktas, and B. Ecer, “GIS-Based Multi-Criteria Decision Making for Site Selection: An Application of GRP Pipe Production Plant,” J. Mult. Valued Log. Soft Comput., vol. 39, pp. 407-429, 2022.
  • A. Aktas, M. Kabak, “Evaluation of energy storage alternatives for hybrid energy systems using a hesitant fuzzy approach,” J. Ind. Manag. Optim., vol. 20, pp. 858-877, 2024.

Yıl 2025, Cilt: 14 Sayı: 2, 930 - 951, 30.06.2025

Koksal Aktas , Ahmet Aktas , Mehmet Kabak

https://doi.org/10.17798/bitlisfen.1621902

Öz

Kaynakça

  • G.S. de Assis, M. dos Santos, and M. P. Basilio, M.P. “Use of the WASPAS Method to Select Suitable Helicopters for Aerial Activity Carried Out by the Military Police of the State of Rio de Janeiro,” Axioms, vol. 12, 77. 2023.
  • S. Iskanderani, O. Bafail, and M. Alamoudi, “Optimizing Sugar Manufacturing: A Hybrid Simulation-Based Approach and MCDM for Efficient Decision Making,” Axioms, 12, 975, 2023.
  • N. V. Thanh, N. T. K. Lan, “A New Hybrid Triple Bottom Line Metrics and Fuzzy MCDM Model: Sustainable Supplier Selection in the Food-Processing Industry,” Axioms, vol. 11, 57, 2022.
  • H.-T. Le, T.-C. Chu, “Ranking Alternatives Using a Fuzzy Preference Relation-Based Fuzzy VIKOR Method,” Axioms, vol. 12, 1079, 2023.
  • H. A. Es, C. Hamzacebi, and S. U. O. Firat, “GRA-TRI: A Multicriteria Decision Aid Classification Method based on Grey Relational Analysis,” J. Grey Syst., vol. 30, pp. 1–12, 2018.
  • M. Çolak, İ. Kaya, “Prioritization of Renewable Energy Alternatives by Using an Integrated Fuzzy MCDM Model: A Real Case Application for Turkey,” Renew. Sustain. Energy Rev., vol. 80, pp. 840–853, 2017.
  • T.-C. Chu, T. B. H. Nghiem, “Extension of Fuzzy ELECTRE I for Evaluating Demand Forecasting Methods in Sustainable Manufacturing,” Axioms, vol. 12, 926, 2023.
  • A. Łuczak, M. A. Just, “Complex MCDM Procedure for the Assessment of Economic Development of Units at Different Government Levels,” Mathematics, vol. 8, 1067, 2020.
  • T. L. Saaty, What is the analytic hierarchy process? In Mathematical Models for Decision Support; Berlin/Heidelberg: Springer, 1988; pp. 109–121.
  • T. L. Saaty, L. G. Vargas. 2006. Decision Making with the Analytic Network Process. Berlin/Heidelberg: Springer, vol. 282.
  • İ. Gölcük, A. Baykasoglu, “An analysis of DEMATEL approaches for criteria interaction handling within ANP,” Expert Syst. Appl., vol. 46, pp. 346–366, 2016.
  • B. Efe, M. A. Yerlikaya, and Ö. F. Efe, “Mobile phone selection based on a novel quality function deployment approach,” Soft Comput., vol. 24, pp. 15447–15461, 2020.
  • A. Yildizbasi, Y. Arioz, “Green supplier selection in new era for sustainability: A novel method for integrating big data analytics and a hybrid fuzzy multi-criteria decision making,” Soft Comput., vol. 26, pp. 253–270, 2022.
  • C. Çetinkaya, M. Kabak, M. Erbaş, and E. Özceylan, “Evaluation of ecotourism sites: A GIS-based multi-criteria decision analysis,” Kybernetes, vol. 47, pp. 1664–1686, 2018.
  • G. Ozkaya, A. Demirhan, “Analysis of Countries in Terms of Artificial Intelligence Technologies: PROMETHEE and GAIA Method Approach,” Sustainability, 15, 4604, 2023.
  • I. Clímaco, C. Henggeler Antunes, “Evaluation of Fiscal and Non-Fiscal Policies for Electric Vehicles—A Multi-Criterion Sorting Approach,” Sustainability, vol. 15, 6213, 2023.
  • T. B. H. Nghiem, T.-C. Chu, “Evaluating Lean Facility Layout Designs Using a BWM-Based Fuzzy ELECTRE I Method,” Axioms, vol. 11, 447, 2022.
  • A. Karasan, F. K. Gündoǧdu, and S. Aydın, “Decision-making methodology by using multi-expert knowledge for uncertain environments: Green metric assessment of universities,” Environ. Dev. Sustain., vol. 25, pp. 7393–7422, 2022.
  • M. A. Yerlikaya, K. Yildiz, and B. N. Keskin, “Solution proposal for completed preference structure in ORESTE method,” Sci Rep, vol. 13, 4754, 2023.
  • S. Aydin, “A Novel Multi-Expert Mabac Method Based on Fermatean Fuzzy Sets,” J. Mult. Valued Log. Soft Comput., vol. 37, pp. 533–552, 2021.
  • G. Özçelik, M. Nalkıran, “An extension of EDAS method equipped with trapezoidal bipolar fuzzy information: An application from healthcare system,” Int. J. Fuzzy Syst., vol. 23, pp. 2348–2366, 2021.
  • S. Gáspár, Z. Musinszki, I. Z. Hágen, Á. Barta, J. Bárczi, and G. Thalmeiner, “Developing a Controlling Model for Analyzing the Subjectivity of Enterprise Sustainability and Expert Group Judgments Using Fuzzy Triangular Membership Functions,” Sustainability, vol. 15, 7981, 2023.
  • K. R. Hindi, A. El-Assal, I. Sabry, “Multi-criteria decision making methods comparative analysis in Fuzzy Environment: article review,” Benha J. Appl. Sci., vol. 7, pp. 227-235, 2022.
  • V. Torra, “Hesitant fuzzy sets,” Int. J. Intell. Syst., vol. 25, pp. 529–539, 2010.
  • M. Yavuz, B. Oztaysi, S. C. Onar, and C. Kahraman, “Multi-criteria evaluation of alternative-fuel vehicles via a hierarchical hesitant fuzzy linguistic model,” Expert Syst. Appl., vol. 42, pp. 2835–2848, 2015.
  • Z. Xu, X. Zhang, “Hesitant fuzzy multi-attribute decision making based on TOPSIS with incomplete weight information,” Knowl.- Based Syst., vol. 52, pp. 53–64, 2013.
  • E. K. Zavadskas, Z. Turskis, “Multiple criteria decision making (MCDM) methods in economics: An overview,” Technol. Econ. Dev. Econ., vol. 17, pp. 397–427, 2011.
  • S.-H. Tsaur, T.-Y. Chang, and C. H. Yen, “The evaluation of airline service quality by fuzzy MCDM,” Tour. Manag. vol. 23, pp. 107–115, 2002.
  • B. D. Rouyendegh, ”The intuitionistic fuzzy ELECTRE model,” Int. J. Manag. Sci. Eng. Manag. vol. 13, pp. 139–145, 2018.
  • A. Pınar, R. Babak Daneshvar, and Y. S. Özdemir, “q-Rung Orthopair Fuzzy TOPSIS Method for Green Supplier Selection Problem,” Sustainability, vol. 13, 985, 2021.
  • K. Zahid, M. Akram, and C. Kahraman, “A new ELECTRE-based method for group decision-making with complex spherical fuzzy information,” Knowl. Based Syst. vol. 243, 108525, 2022.
  • A. V. Ertemel, A. Menekse, and H. Camgoz Akdag, “Smartphone Addiction Assessment Using Pythagorean Fuzzy CRITIC-TOPSIS,” Sustainability, vol. 15, 3955, 2023.
  • S. Cebi, F. Kutlu Gündoğdu, and C. Kahraman, “Consideration of reciprocal judgments through Decomposed Fuzzy Analytical Hierarchy Process: A case study in the pharmaceutical industry,” Appl. Soft Comput., vol. 134, 110000, 2023.
  • A. Aktas, B. Ecer, and M. Kabak, “A Hybrid Hesitant Fuzzy Model for Healthcare Systems Ranking of European Countries,” Systems, vol. 10, 219, 2022.
  • R. M. Rodriguez, L. Martinez, L. and F. Herrera, “Hesitant fuzzy linguistic term sets for decision making,” IEEE Trans. Fuzzy Syst., vol. 20, pp. 109–119, 2012.
  • C. L. Hwang, K. Yoon, Multiple Attribute Decision Making: Methods and Applications, A State of the Art Survey; New York, NY: Springer, 1981.
  • Z. Xu, M. Xia, “On Distance and Correlation Measures of Hesitant Fuzzy Information,” Int. J. Intell. Syst, vol. 26, pp. 410–425, 2011.
  • J. Dong, T.-T. Feng, Y.-S. Yang, and Y. Ma, “Macro-site selection of wind/solar hybrid power station based on ELECTRE-II,” Renew. Sustain. Energy Rev., vol. 35, pp. 194–204, 2014.
  • N. C. Chatterjee, G. K. Bose, “A COPRAS-F base multi-criteria group decision making approach for site selection of wind farm,” Decis. Sci. Lett., vol. 2, pp. 1–10, 2013.
  • T. Kaya, C. Kahraman, “Multicriteria renewable energy planning using an integrated fuzzy VIKOR & AHP methodology: The case of Istanbul”, Energy, vol. 35, pp. 2517–2527, 2010.
  • I. Talinli, E. Topuz, E. Aydin, and S. B. Kabakcı, “A Holistic Approach for Wind Farm Site Selection by FAHP”, IntechOpen. Available online: https://www.researchgate.net/publication/221912736_A_Holistic_Approach_for_Wind_Farm_Site_Selection_by_Using_FAHP
  • S. Cebi, C. Kahraman, “Using Multi Attribute Choquet Integral in Site Selection of Wind Energy Plants: The Case of Turkey,” J. Mult. Valued Log. Soft Comput., vol. 20, 423–443, 2013.
  • M.S. Kang, C.S. Chen, Y.L. Ke, A.H. Lee, T.T. Ku, and H.Y. Kang, “Applications of FANP and BOCR in renewable energy-study on the choice of the sites for wind farms,” IEEE Trans. Ind. Appl., vol. 49, pp. 982–989, 2013.
  • W. Yun-Na, Y. Yi-Sheng, F. Tian-Tian, K. Li-Na, L. Wei, and F. Luo-Jie, “Macro-site selection of wind/solar hybrid power sta-tion based on Ideal Matter-Element Model,” Int. J. Electr. Power Energy Syst., vol. 50, pp. 76–84, 2013.
  • R. Van Haaren, V. Fthenakis, “GIS-based wind farm site selection using spatial multi-criteria analysis (SMCA): Evaluating the case for New York State,” Renew. Sustain. Energy Rev., vol. 15, pp. 3332–3340, 2011.
  • R. H. A. Hamid, “A GIS-DSS for wind farms industry in Egypt,” 2011 International Conference & Utility Exhibition on Power and Energy Systems: Issues and Prospects for Asia (ICUE), Pattaya, Thailand, 28-30 September 2011.
  • L. Selcuk, “An avalanche hazard model for Bitlis Province, Turkey, using GIS based multicriteria decision analysis,” Turk. J. Earth Sci., vol. 22, pp. 523–535, 2013.
  • M. Kabak, H. Javadi, A. Aktas, and B. Ecer, “GIS-Based Multi-Criteria Decision Making for Site Selection: An Application of GRP Pipe Production Plant,” J. Mult. Valued Log. Soft Comput., vol. 39, pp. 407-429, 2022.
  • A. Aktas, M. Kabak, “Evaluation of energy storage alternatives for hybrid energy systems using a hesitant fuzzy approach,” J. Ind. Manag. Optim., vol. 20, pp. 858-877, 2024.
Toplam 49 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Endüstri Mühendisliği
Bölüm Research Article
Yazarlar

Koksal Aktas 0009-0002-4085-779X

Ahmet Aktas 0000-0002-4394-121X

Mehmet Kabak 0000-0002-8576-5349

Erken Görünüm Tarihi 27 Haziran 2025
Yayımlanma Tarihi 30 Haziran 2025
Gönderilme Tarihi 17 Ocak 2025
Kabul Tarihi 31 Mart 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 14 Sayı: 2

Kaynak Göster

IEEE K. Aktas, A. Aktas, ve M. Kabak, “An Integrated HFLTS and HF-TOPSIS Approach for Wind Turbine Site Selection Problem”, Bitlis Eren Üniversitesi Fen Bilimleri Dergisi, c. 14, sy. 2, ss. 930–951, 2025, doi: 10.17798/bitlisfen.1621902.
 Kapak Resmi İndir

Bitlis Eren University
Journal of Science Editor
Bitlis Eren University Graduate Institute
Bes Minare Mah. Ahmet Eren Bulvari, Merkez Kampus, 13000 BITLIS