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WEIGHTING THE UNIVERSAL DESIGN PRINCIPLES USING MULTI-CRITERIA DECISION MAKING TECHNIQUES

Yıl 2020, Cilt: 8 Sayı: 1, 105 - 118, 20.03.2020
https://doi.org/10.21923/jesd.427505

Öz

Universal Design (UD) is the design of products and environments that can be used by all people in the widest possible way without the need for adaptation and custom design. It involves a wide range of design disciplines, including environments, products, and communication design. A working group of developers (architects, product designers and environmental design researchers) guided the design process without evaluating existing designs and identified seven UD principles to be used to educate designers and consumers about the properties of more useful products and environments. These principles are “Equitable Use”, “Flexibility in Use”, “Simple and Intuitive Use”, “Perceptible Information”, “Tolerance for Error”, “Low Physical Effort”, and “Size and Space for Approach and Use”. Prioritizing or weighting these principles can be handled as a Multi Criteria Decision Making (MCDM) problem. For this reason, in this paper we study the prioritizing of these principles using two of MCDM techniques with fuzzy numbers, namely AHP and ANP, and the results of both algorithms are compared. The main contribution of this paper is to prioritize UD principles using numerical methods with experts’ view. This work, which includes grading the principle 7 of Universal Design in itself, will be guiding for designers. To the authors’ knowledge, this will be the first interdisciplinary study which uses these two techniques for evaluating UD principles for developers.

Kaynakça

  • ADA standards for Accessible Design. 1994. 28 CFR Part 36.
  • Afacan, Y., Demirkan, H., 2010. A priority-based approach for satisfying the diverse users’ needs, capabilities and expectations: a universal kitchen design case. Journal of Engineering Design 21, 315-343.
  • Alias, M. A., Hashim, S. Z. M., Samsudin, S., 2009. Using fuzzy analytic hierarchy process for southern Johor river ranking. International Journal of Advances in Soft Computing and its Applications 1(1), 62-76.
  • Andric, J. M., Lu, D. G., 2016. Risk assessment of bridges under multiple hazards in operation period. Safety Science 83, 80–92.
  • Aslaksen, F., Bergh, S., Bringa, O.R., Heggem, E.K., 1997. Universal Design and Design for All, Cornell University ILR School, Gladnet Collection, Norwegian.
  • Ayag, Z., Ozdemir, R. G., 2007. An intelligent approach to ERP software selection through fuzzy ANP. International Journal of Production Research 45, 2169-2194.
  • Bianchin, M., Heylighen, A., 2018. Just design, Design Studies 54, 1-22.
  • Bitarafan, M., Hashemkhani Zolfani, S., Arefi, S. L., Zavadskas, E. K., 2012. Evaluating the construction methods of cold-formed steel structures in reconstructing the areas damaged in natural crises, using the methods AHP and COPRAS-G. Archives of Civil and Mechanical Engineering 12, 360–367.
  • British Standard Draft. 2004. Design Management Systems, 7000-6.
  • Boender, C. G. E., De Graan, J. G., Lootsma, F. A., 1989. Multicriteria decision analysis with fuzzy pairwise comparisons. Fuzzy Sets and Systems 29, 133-143.
  • Buckley, J. J., 1985a. Ranking alternatives using fuzzy members. Fuzzy Sets and Systems 15, 21-31.
  • Buckley, J. J., 1985b. Fuzzy hierarchical analysis. Fuzzy Sets and Systems 17, 233-247.
  • Buyukozkan, G., Ertay, T., Kahraman, C., Ruan, D., 2004. Determining the Importance Weights for the Design Requirements in the House of Quality Using the Fuzzy Analytic Network Approach. International Journal of Intelligent Systems 19, 443-461.
  • Buyukozkan, G., Feyzioglu, O., Nebol, E., 2008. Selection of the strategic alliance partner in logistics value chain. International Journal of Production Economics 113, 148-158.
  • Cascales, M. S. G., Lamata, M. T., 2008. Fuzzy analytical hierarchy process in maintenance problem. In Nguyen NT (eds) IEA/AIE 2008, LNAI 5027. Berlin: Springer-Verlag.
  • Center for Universal Design., 1997. Environments and products for all people. Raleigh: North Carolina State University, Center for Universal Design. Accessed 25/05/2017, from http://www.design.ncsuedu/cud/univ_design/ud.htm.
  • Chang, D. Y., 1996. Applications of the extent analysis method on fuzzy AHP. European Journal of Operational Research 95, 649-655.
  • Chou, J.R., 2012. A linguistic evaluation approach for universal design. Information Sciences 190, 76-94.
  • Demirel, T., Cetin Demirel, N., Ozdemir, Y., 2010. Prioritization of Tourism Types Using Fuzzy Analytic Network Process. World Scientific Proceedings Series on Computer Engineering and Information Science 2, 514-519.
  • Ebrahimnejad, S., Mousavi, S. M., Tavakkoli-Moghaddam, R., Hashemi, H., Vahdani, B., 2012. A novel two-phase group decision making approach for construction project selection in a fuzzy environment. Applied Mathematical Modelling 36, 4197-4217.
  • Ertay, T., Büyüközkan, G., Kahraman, C., Ruan, D., 2005. Quality function deployment implementation based on Analytic Network Process with linguistic data: An application in automotive industry. Journal of Intelligent & Fuzzy Systems 16, 221-232.
  • Haghighi, M., Divandari, A., Keimasi, M., 2010. The impact of 3D e-readiness on e-banking development in Iran: A fuzzy AHP analysis. Expert Systems with Applications 37, 4084-4093.
  • Hogan, P., 2004. Good Design Enables, Bad Design Disables, EIDDDesign for All Declaration. Internal draft.
  • Hsieh, T. Y., Lu, S. T., Tzeng, G. H., 2004. Fuzzy MCDM approach for planning and design tenders selection in public office buildings. International Journal of Project Management 22, 573-584.
  • Hung, Y. H., Huang, M. L., Fanchiang, K. L., 2012. Applying the fuzzy analytic network process to the selection of an advanced integrated circuit (IC) packaging process development project. International Journal of the Physical Sciences 7, 281-296.
  • Kahraman, C., Cebeci, U., Ruan, D., 2004. Multi-attribute comparison of catering service companies using fuzzy AHP: The case of Turkey. International Journal of Production Economics 87(2), 171–184.
  • Kaya, T., Kahraman, C., 2011. An integrated fuzzy AHP-ELECTRE methodology for environmental impact assessment. Expert System with Application 38, 8553-8562.
  • Kog, F., Yaman, H., 2014. A meta classification and analysis of contractor selection and prequalification. Procedia Engineering 85, 302-310.
  • Laarhoven, P. J. M., Pedrycz, W., 1983. A fuzzy extension of Saaty’s priority theory. Fuzzy Sets and Systems 11, 229-241.
  • Lootsma, F., 1997. Fuzzy Logic for Planning and Decision-Making. Dordrecht: Kluwer.
  • Mace, R. L., Hardie, G. J., Place, J. P., 1991. Accesible Environments: Towards Universal Design. Innovation by Design. W.E. Preiser, J.C. Vischer, E.T. White (Eds.). Van Nostrand Reinhold, New York.
  • Mahmoodzadeh, S., Shahrabi, J., Pariazar, M., Zaeri, M. S., 2007. Project selection by using fuzzy AHP and TOPSIS technique. International Journal of Social, Human Science and Engineering 1(6), 302-307.
  • Meade, L., Sarkis, J., 1998. Strategic analysis of logistics and supply chain management systems using the analytical network process. Transportation Research Part E: Logistics and Transportation Review 34, 201-215.
  • Mikhailov, L., 2003. Deriving priorities from fuzzy pairwise comparison judgments. Fuzzy Sets and Systems 134, 365-385.
  • Mikhailov, L., Singh, M. G., 2003. Fuzzy analytic network process and its application to the development of decision support systems. IEEE Transaction on Systems, Man, and Cybernetics-Part C: Applications and Reviews 33, 33-41.
  • Mikhailov, L., Tsvetinov, P., 2004. Evaluation of services using a fuzzy analytic hierarchy process. Applied Soft Computing 5(1), 23–33.
  • Mohanty, R. P., Agarwal, R., Choudhury, A. K., Tiwari, M. K., 2005. A Fuzzy ANP–based approach to R&D project selection: A case study. International Journal of Production Research 43, 5199-5216.
  • Nassar, K., Thabet, W., Beliveau, Y., 2003. A procedure for multi-criteria selection of building assemblies. Automation in Construction 12, 543-560.
  • Nieto-Morote, A., Ruz-Vila, F., 2011. A fuzzy approach to construction project risk assessment. International Journal of Project Management 29, 220–231.
  • Ozdagoglu, A., Ozdagoglu, G., 2007. Comparison of AHP and fuzzy AHP for the multicriteria decision making processes with linguistic evaluations. Istanbul Commerce University Fen Bilimleri Dergisi 11, 65-85.
  • Ozdemir, S., Ozdemir, Y., 2018. Prioritizing store plan alternatives produced with shape grammar using multi-criteria decision making techniques. Environment and Planning B: Urban Analytics and City Science 45(4), 751-771. Oztaysi, B., Kaya, T., Kahraman, C., 2011. Performance comparison based on customer relationship management using analytic network process. Expert Systems with Applications 38, 9788-9798.
  • Oztaysi, B., Ugurlu, S., Kahraman, C., 2013. Assessment of Green Energy Alternatives Using Fuzzy ANP. In Cavallaro F (eds), Assessment and Simulation Tools for Sustainable Energy Systems (pp. 55-77). London: Springer.
  • Pan, N. F., 2008. Fuzzy AHP approach for selecting the suitable bridge construction method. Automation in Construction 17, 958–965.
  • Pan, N. F., 2009. Selecting an appropriate excavation construction method based on qualitative assessments. Expert Systems with Applications 36, 5481–5490.
  • Pohekar, S. D., Ramachandran, M., 2004. Application of Multi-criteria Decision Making to Sustainable Energy Planning-A Review. Renewable and Sustainable Energy Reviews 8, 365-381.
  • Promentilla, M. A. B., Furuichi, T., Ishii, K., Tanikawa, N., 2006. Evaluation of remedial countermeasures using the analytic network process. Waste Management 26, 1410-1421.
  • Promentilla, M. A. B., Furuichi, T., Ishii, K., Tanikawa, N., 2008. A fuzzy analytic network process for multi-criteria evaluation of contaminated site remedial countermeasures. Journal of Environmental Management 88, 479-495.
  • Ribeiro, R. A., 1996. Fuzzy multiple criterion decision making: A review and new preference elicitation techniques. Fuzzy Sets and Systems 78, 155-181.
  • Rodríguez, A., Ortega, F., Concepción, R., 2013. A method for the selection of customized equipment suppliers. Expert Systems with Applications 40(4), 1170–1176.
  • Saaty, T. L., 1980. The Analytic Hierarchy Process. New York: McGraw Hill.
  • Shapira, A., Goldenberg, M., 2005. AHP-Based Equipment Selection Model for Construction Projects. Journal of Construction Engineering and Management 131(12), 1263-1273.
  • Story, M. F., Mueller, J., Mace, R. L., 2001. The Universal Design File: Designing for People of all ages and Abilities. Raleigh, North Carolina State University, USA.
  • Taylan, O., Bafail, A. O., Abdulaal, R. M. S., Kabli, M. R., 2014. Construction projects selection and risk assessment by fuzzy AHP and fuzzy TOPSIS methodologies. Applied Soft Computing 17, 105–116.
  • Tuzkaya, G., Gulsun, B., Kahraman, C., Ozgen, D., 2010. An integrated fuzzy multi-criteria decision making methodology for material handling equipment selection problem and an application. Expert Systems with Applications 37, 2853-2863.
  • Tuzkaya, U. R., Onut, S., 2008. A fuzzy analytic network process based approach to transportation-mode selection between Turkey and Germany: A case study. Information Sciences 178, 3133-3146.
  • Yasmin, F., Kumar, A., Kumar, A., 2013. Fuzzy Theory Concept Applied in Analytic Network Process. International Journal of Advanced Research in Computer Science and Software Engineering 3, 832-837.
  • Yellepeddi, S., 2006. An Analytical Network Process (ANP) approach for the development of a reverse supply chain performance index in consumer electronics industry. PhD Dissertation, The University of Texas, USA.
  • Yılmaz Kaya, B., Dağdeviren, M., 2016. Selecting Occupational Safety Equipment by MCDM Approach Considering Universal Design Principles. Human Factors and Ergonomics in Manufacturing & Service Industries 26(2), 224-242.
  • Wijk, M., 1997. Differences we Share, Faculty of Architecture, Delft University of Technology, Netherlands.
  • Zadeh, L. A., 1965. Fuzzy Sets. Information and Control 8, 338-353.
  • Zeng, J., An, M., Smith, N. J., 2007. Application of a fuzzy based decision making methodology to construction project risk assessment. International Journal of Project Management 25, 589–600.
  • Zhou, X., Lv, B., Lu, M., 2013. ERP System Flexibility Measurement Based on Fuzzy Analytic Network Process. Journal of Software 8, 1943-1951.

ÇOK KRİTERLİ KARAR VERME TEKNİKLERİ KULLANILARAK EVRENSEL TASARIM İLKELERİNİN AĞIRLIKLANDIRILMASI

Yıl 2020, Cilt: 8 Sayı: 1, 105 - 118, 20.03.2020
https://doi.org/10.21923/jesd.427505

Öz

Evrensel Tasarım (UD), adaptasyon ve özel tasarım gerekmeden tüm insanlar tarafından en geniş şekilde kullanılabilecek ürün ve ortamların tasarımıdır. Ortamlar, ürünler ve iletişim tasarımı dahil olmak üzere çok çeşitli tasarım disiplinlerini içerir. Uzmanlardan oluşan bir çalışma grubu (mimarlar, ürün tasarımcıları ve çevre tasarım araştırmacıları), tasarım sürecini mevcut tasarımları değerlendirerek, tasarımcıları ve tüketicileri daha yararlı ürünlerin ve ortamların özellikleri hakkında eğitmek için kullanılacak yedi UD ilkesini belirlemiştir. Bu ilkeler “Eşit Kullanım”, ”Kullanımda Esneklik”, “Basit ve Sezgisel Kullanım”, “Algılanabilir Bilgi”, “Hatalara Dayanım”, “Düşük Fiziksel Çaba” ve “Yaklaşım ve Kullanım için Boyut ve Mekan” dır. Bu ilkelerin önceliklendirilmesi veya ağırlıklandırılması, Çok Kriterli Karar Verme (ÇKKV) yöntemi ile ele alınmıştır. Bu çalışmada, bu ilkelerin, ÇKKV yöntemleri olan AHP ve ANP yöntemleri, bulanık sayılar kullanılarak önceliklendirilmiş ve her iki yöntemin sonuçları karşılaştırılmıştır. Bu çalışmanın ana fikri, uzmanların görüşleri ile sayısal yöntemler kullanılarak Evrensel Tasarım ilkelerini ağırlıklandırmaktır. Evrensel tasarımın 7 ilkesini kendi içinde derecelendirmeyi içeren bu çalışma, tasarımcılar için yol gösterici olacaktır. Yazarların bilgisine göre bu çalışma, Evrensel Tasarım ilkelerini, uzman görüşlerine göre bu teknikler kullanılarak ağırlıklandıran literatürdeki ilk disiplinlerarası çalışma olacaktır. 

Kaynakça

  • ADA standards for Accessible Design. 1994. 28 CFR Part 36.
  • Afacan, Y., Demirkan, H., 2010. A priority-based approach for satisfying the diverse users’ needs, capabilities and expectations: a universal kitchen design case. Journal of Engineering Design 21, 315-343.
  • Alias, M. A., Hashim, S. Z. M., Samsudin, S., 2009. Using fuzzy analytic hierarchy process for southern Johor river ranking. International Journal of Advances in Soft Computing and its Applications 1(1), 62-76.
  • Andric, J. M., Lu, D. G., 2016. Risk assessment of bridges under multiple hazards in operation period. Safety Science 83, 80–92.
  • Aslaksen, F., Bergh, S., Bringa, O.R., Heggem, E.K., 1997. Universal Design and Design for All, Cornell University ILR School, Gladnet Collection, Norwegian.
  • Ayag, Z., Ozdemir, R. G., 2007. An intelligent approach to ERP software selection through fuzzy ANP. International Journal of Production Research 45, 2169-2194.
  • Bianchin, M., Heylighen, A., 2018. Just design, Design Studies 54, 1-22.
  • Bitarafan, M., Hashemkhani Zolfani, S., Arefi, S. L., Zavadskas, E. K., 2012. Evaluating the construction methods of cold-formed steel structures in reconstructing the areas damaged in natural crises, using the methods AHP and COPRAS-G. Archives of Civil and Mechanical Engineering 12, 360–367.
  • British Standard Draft. 2004. Design Management Systems, 7000-6.
  • Boender, C. G. E., De Graan, J. G., Lootsma, F. A., 1989. Multicriteria decision analysis with fuzzy pairwise comparisons. Fuzzy Sets and Systems 29, 133-143.
  • Buckley, J. J., 1985a. Ranking alternatives using fuzzy members. Fuzzy Sets and Systems 15, 21-31.
  • Buckley, J. J., 1985b. Fuzzy hierarchical analysis. Fuzzy Sets and Systems 17, 233-247.
  • Buyukozkan, G., Ertay, T., Kahraman, C., Ruan, D., 2004. Determining the Importance Weights for the Design Requirements in the House of Quality Using the Fuzzy Analytic Network Approach. International Journal of Intelligent Systems 19, 443-461.
  • Buyukozkan, G., Feyzioglu, O., Nebol, E., 2008. Selection of the strategic alliance partner in logistics value chain. International Journal of Production Economics 113, 148-158.
  • Cascales, M. S. G., Lamata, M. T., 2008. Fuzzy analytical hierarchy process in maintenance problem. In Nguyen NT (eds) IEA/AIE 2008, LNAI 5027. Berlin: Springer-Verlag.
  • Center for Universal Design., 1997. Environments and products for all people. Raleigh: North Carolina State University, Center for Universal Design. Accessed 25/05/2017, from http://www.design.ncsuedu/cud/univ_design/ud.htm.
  • Chang, D. Y., 1996. Applications of the extent analysis method on fuzzy AHP. European Journal of Operational Research 95, 649-655.
  • Chou, J.R., 2012. A linguistic evaluation approach for universal design. Information Sciences 190, 76-94.
  • Demirel, T., Cetin Demirel, N., Ozdemir, Y., 2010. Prioritization of Tourism Types Using Fuzzy Analytic Network Process. World Scientific Proceedings Series on Computer Engineering and Information Science 2, 514-519.
  • Ebrahimnejad, S., Mousavi, S. M., Tavakkoli-Moghaddam, R., Hashemi, H., Vahdani, B., 2012. A novel two-phase group decision making approach for construction project selection in a fuzzy environment. Applied Mathematical Modelling 36, 4197-4217.
  • Ertay, T., Büyüközkan, G., Kahraman, C., Ruan, D., 2005. Quality function deployment implementation based on Analytic Network Process with linguistic data: An application in automotive industry. Journal of Intelligent & Fuzzy Systems 16, 221-232.
  • Haghighi, M., Divandari, A., Keimasi, M., 2010. The impact of 3D e-readiness on e-banking development in Iran: A fuzzy AHP analysis. Expert Systems with Applications 37, 4084-4093.
  • Hogan, P., 2004. Good Design Enables, Bad Design Disables, EIDDDesign for All Declaration. Internal draft.
  • Hsieh, T. Y., Lu, S. T., Tzeng, G. H., 2004. Fuzzy MCDM approach for planning and design tenders selection in public office buildings. International Journal of Project Management 22, 573-584.
  • Hung, Y. H., Huang, M. L., Fanchiang, K. L., 2012. Applying the fuzzy analytic network process to the selection of an advanced integrated circuit (IC) packaging process development project. International Journal of the Physical Sciences 7, 281-296.
  • Kahraman, C., Cebeci, U., Ruan, D., 2004. Multi-attribute comparison of catering service companies using fuzzy AHP: The case of Turkey. International Journal of Production Economics 87(2), 171–184.
  • Kaya, T., Kahraman, C., 2011. An integrated fuzzy AHP-ELECTRE methodology for environmental impact assessment. Expert System with Application 38, 8553-8562.
  • Kog, F., Yaman, H., 2014. A meta classification and analysis of contractor selection and prequalification. Procedia Engineering 85, 302-310.
  • Laarhoven, P. J. M., Pedrycz, W., 1983. A fuzzy extension of Saaty’s priority theory. Fuzzy Sets and Systems 11, 229-241.
  • Lootsma, F., 1997. Fuzzy Logic for Planning and Decision-Making. Dordrecht: Kluwer.
  • Mace, R. L., Hardie, G. J., Place, J. P., 1991. Accesible Environments: Towards Universal Design. Innovation by Design. W.E. Preiser, J.C. Vischer, E.T. White (Eds.). Van Nostrand Reinhold, New York.
  • Mahmoodzadeh, S., Shahrabi, J., Pariazar, M., Zaeri, M. S., 2007. Project selection by using fuzzy AHP and TOPSIS technique. International Journal of Social, Human Science and Engineering 1(6), 302-307.
  • Meade, L., Sarkis, J., 1998. Strategic analysis of logistics and supply chain management systems using the analytical network process. Transportation Research Part E: Logistics and Transportation Review 34, 201-215.
  • Mikhailov, L., 2003. Deriving priorities from fuzzy pairwise comparison judgments. Fuzzy Sets and Systems 134, 365-385.
  • Mikhailov, L., Singh, M. G., 2003. Fuzzy analytic network process and its application to the development of decision support systems. IEEE Transaction on Systems, Man, and Cybernetics-Part C: Applications and Reviews 33, 33-41.
  • Mikhailov, L., Tsvetinov, P., 2004. Evaluation of services using a fuzzy analytic hierarchy process. Applied Soft Computing 5(1), 23–33.
  • Mohanty, R. P., Agarwal, R., Choudhury, A. K., Tiwari, M. K., 2005. A Fuzzy ANP–based approach to R&D project selection: A case study. International Journal of Production Research 43, 5199-5216.
  • Nassar, K., Thabet, W., Beliveau, Y., 2003. A procedure for multi-criteria selection of building assemblies. Automation in Construction 12, 543-560.
  • Nieto-Morote, A., Ruz-Vila, F., 2011. A fuzzy approach to construction project risk assessment. International Journal of Project Management 29, 220–231.
  • Ozdagoglu, A., Ozdagoglu, G., 2007. Comparison of AHP and fuzzy AHP for the multicriteria decision making processes with linguistic evaluations. Istanbul Commerce University Fen Bilimleri Dergisi 11, 65-85.
  • Ozdemir, S., Ozdemir, Y., 2018. Prioritizing store plan alternatives produced with shape grammar using multi-criteria decision making techniques. Environment and Planning B: Urban Analytics and City Science 45(4), 751-771. Oztaysi, B., Kaya, T., Kahraman, C., 2011. Performance comparison based on customer relationship management using analytic network process. Expert Systems with Applications 38, 9788-9798.
  • Oztaysi, B., Ugurlu, S., Kahraman, C., 2013. Assessment of Green Energy Alternatives Using Fuzzy ANP. In Cavallaro F (eds), Assessment and Simulation Tools for Sustainable Energy Systems (pp. 55-77). London: Springer.
  • Pan, N. F., 2008. Fuzzy AHP approach for selecting the suitable bridge construction method. Automation in Construction 17, 958–965.
  • Pan, N. F., 2009. Selecting an appropriate excavation construction method based on qualitative assessments. Expert Systems with Applications 36, 5481–5490.
  • Pohekar, S. D., Ramachandran, M., 2004. Application of Multi-criteria Decision Making to Sustainable Energy Planning-A Review. Renewable and Sustainable Energy Reviews 8, 365-381.
  • Promentilla, M. A. B., Furuichi, T., Ishii, K., Tanikawa, N., 2006. Evaluation of remedial countermeasures using the analytic network process. Waste Management 26, 1410-1421.
  • Promentilla, M. A. B., Furuichi, T., Ishii, K., Tanikawa, N., 2008. A fuzzy analytic network process for multi-criteria evaluation of contaminated site remedial countermeasures. Journal of Environmental Management 88, 479-495.
  • Ribeiro, R. A., 1996. Fuzzy multiple criterion decision making: A review and new preference elicitation techniques. Fuzzy Sets and Systems 78, 155-181.
  • Rodríguez, A., Ortega, F., Concepción, R., 2013. A method for the selection of customized equipment suppliers. Expert Systems with Applications 40(4), 1170–1176.
  • Saaty, T. L., 1980. The Analytic Hierarchy Process. New York: McGraw Hill.
  • Shapira, A., Goldenberg, M., 2005. AHP-Based Equipment Selection Model for Construction Projects. Journal of Construction Engineering and Management 131(12), 1263-1273.
  • Story, M. F., Mueller, J., Mace, R. L., 2001. The Universal Design File: Designing for People of all ages and Abilities. Raleigh, North Carolina State University, USA.
  • Taylan, O., Bafail, A. O., Abdulaal, R. M. S., Kabli, M. R., 2014. Construction projects selection and risk assessment by fuzzy AHP and fuzzy TOPSIS methodologies. Applied Soft Computing 17, 105–116.
  • Tuzkaya, G., Gulsun, B., Kahraman, C., Ozgen, D., 2010. An integrated fuzzy multi-criteria decision making methodology for material handling equipment selection problem and an application. Expert Systems with Applications 37, 2853-2863.
  • Tuzkaya, U. R., Onut, S., 2008. A fuzzy analytic network process based approach to transportation-mode selection between Turkey and Germany: A case study. Information Sciences 178, 3133-3146.
  • Yasmin, F., Kumar, A., Kumar, A., 2013. Fuzzy Theory Concept Applied in Analytic Network Process. International Journal of Advanced Research in Computer Science and Software Engineering 3, 832-837.
  • Yellepeddi, S., 2006. An Analytical Network Process (ANP) approach for the development of a reverse supply chain performance index in consumer electronics industry. PhD Dissertation, The University of Texas, USA.
  • Yılmaz Kaya, B., Dağdeviren, M., 2016. Selecting Occupational Safety Equipment by MCDM Approach Considering Universal Design Principles. Human Factors and Ergonomics in Manufacturing & Service Industries 26(2), 224-242.
  • Wijk, M., 1997. Differences we Share, Faculty of Architecture, Delft University of Technology, Netherlands.
  • Zadeh, L. A., 1965. Fuzzy Sets. Information and Control 8, 338-353.
  • Zeng, J., An, M., Smith, N. J., 2007. Application of a fuzzy based decision making methodology to construction project risk assessment. International Journal of Project Management 25, 589–600.
  • Zhou, X., Lv, B., Lu, M., 2013. ERP System Flexibility Measurement Based on Fuzzy Analytic Network Process. Journal of Software 8, 1943-1951.
Toplam 62 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik
Bölüm Araştırma Makalesi \ Research Makaleler
Yazarlar

Yavuz Özdemir 0000-0001-6821-9867

Şahika Özdemir 0000-0002-5762-1962

Yayımlanma Tarihi 20 Mart 2020
Gönderilme Tarihi 27 Mayıs 2018
Kabul Tarihi 27 Kasım 2019
Yayımlandığı Sayı Yıl 2020 Cilt: 8 Sayı: 1

Kaynak Göster

APA Özdemir, Y., & Özdemir, Ş. (2020). WEIGHTING THE UNIVERSAL DESIGN PRINCIPLES USING MULTI-CRITERIA DECISION MAKING TECHNIQUES. Mühendislik Bilimleri Ve Tasarım Dergisi, 8(1), 105-118. https://doi.org/10.21923/jesd.427505