Year 2019, Volume 23, Issue 2, Pages 139 - 148 2019-04-01

The Importance of The Place of Defuzzification Step In Fuzzy Systems

Yakup Çelikbilek [1]

106 218

Fuzzy logic and fuzzy based techniques are applied constantly in both social sciences and engineering sciences for fuzzy systems. However, theoretical content is neglected occasionally in these developed methods. Even sometimes, propositions and applications are developed by using fuzzy numbers ignoring theoretical contents. In some cases, there are lots of different fuzzy solution propositions of same crisp method. Because of these, despite applying similar methods to same data set, very different results can be obtained. Fuzzy multi criteria decision making method propositions are evaluated by using simulation technique in this study to explore and compare the results of fuzzy applications. Simulation applications are applied to AHP, TOPSIS, VIKOR and MOORA methods which are the most common multi criteria decision making methods as both crisp and fuzzy in the literature. Obtained results are evaluated and interpreted for both selection of the best alternative and ranking of all alternatives.
Fuzzy systems, fuzzy numbers, defuzzification, multi criteria decision making, simulation
  • Saaty, T. L., Analytic Heirarchy Process. Wiley StatsRef: Statistics Reference Online, 1980.
  • Chen, Y. C., Yu, T. H., Tsui, P. L., and Lee, C. S., “A fuzzy AHP approach to construct international hotel spa atmosphere evaluation model”, Quality & Quantity, vol. 48, no. 2, pp. 645-657, 2014.
  • Somsuk, N., and Laosirihongthong, T., “A fuzzy AHP to prioritize enabling factors for strategic management of university business incubators: Resource-based view”, Technological forecasting and social change, vol. 85, pp. 198-210, 2014.
  • Mangla, S. K., Kumar, P., and Barua, M. K., “Risk analysis in green supply chain using fuzzy AHP approach: A case study”, Resources, Conservation and Recycling, vol. 104, pp. 375-390, 2015.
  • Gupta, H., and Barua, M., “Fuzzy AHP approach to prioritize enablers of green supply chain management practices: A case study of automotive component supplier”, Management Science Letters, vol. 6, no. 7, pp. 487-498, 2016.
  • Tyagi, S., Agrawal, S., Yang, K., and Ying, H., “An extended Fuzzy-AHP approach to rank the influences of socialization-externalization-combination-internalization modes on the development phase”, Applied Soft Computing, vol. 52, pp. 505-518, 2017.
  • Li, X., Fan, Y., Shaw, J. W., and Qi, Y., “A Fuzzy AHP Approach to Compare Transit System Performance in US Urbanized Areas”, Journal of Public Transportation, vol. 20, no. 2, pp. 66-89, 2017.
  • Yadav, G., and Desai, T. N., “A fuzzy AHP approach to prioritize the barriers of integrated Lean Six Sigma”, International Journal of Quality & Reliability Management, vol. 34, no. 8, pp. 1167-1185, 2017.
  • Vatansever, K., and Kazançoğlu, Y., “Integrated usage of fuzzy multi criteria decision making techniques for machine selection problems and an application”, International Journal of Business and Social Science, vol. 5, no. 9, pp. 12–24, 2014.
  • Hosseini, M. H., and Keshavarz, E., “Using fuzzy AHP and fuzzy TOPSIS for strategic analysis measurement of service quality in banking industry”, International Journal of Applied Management Science, vol. 9, no. 1, pp. 55-80, 2017.
  • Khurram Ali, H. M., Sultan, A., and Rana, B. B., “Captive Power Plant Selection for Pakistan Cement Industry in Perspective of Current Energy Crises: A Fuzzy-AHP Approach”, Mehran University Research Journal of Engineering and Technology, vol. 36, no. 4, pp. 769-780, 2017.
  • Çelikbilek, Y, Adıgüzel Tüylü, A. N., and Esnaf, Ş., “Industrial Coffee Machine Selection with the Fuzzy Analytic Hierarchy Process”, International Journal of Management and Applied Science, vol. 2, no. 2, pp. 20–23, 2016.
  • Hwang, C. L., and Yoon, K., “Methods for multiple attribute decision making”, In Multiple attribute decision making, pp. 58-191, Springer, Berlin, Heidelberg, 1981.
  • Yong, D., “Plant location selection based on fuzzy TOPSIS”, The International Journal of Advanced Manufacturing Technology, vol. 28, no. 7-8, pp. 839-844, 2006.
  • Wang, T. C., and Lee, H. D., “Developing a fuzzy TOPSIS approach based on subjective weights and objective weights”, Expert systems with applications, vol. 36, no. 5, pp. 8980-8985, 2009.
  • Amiri, M. P., “Project selection for oil-fields development by using the AHP and fuzzy TOPSIS methods”, Expert Systems with Applications, vol. 37, no. 9, pp. 6218-6224, 2010.
  • Büyüközkan, G., and Çifçi, G., “A novel hybrid MCDM approach based on fuzzy DEMATEL, fuzzy ANP and fuzzy TOPSIS to evaluate green suppliers”, Expert Systems with Applications, vol. 39, no. 3, pp. 3000-3011, 2012.
  • İç, Y. T., Özel, M., and Kara, İ., “An Integrated Fuzzy TOPSIS-Knapsack Problem Model for Order Selection in a Bakery”, Arabian Journal for Science and Engineering, vol. 42, no. 12, pp. 5321-5337, 2017.
  • Sharma, P., and Singhal, S., “Implementation of fuzzy TOPSIS methodology in selection of procedural approach for facility layout planning”, The International Journal of Advanced Manufacturing Technology, vol. 88, no. 5-8, pp. 1485-1493, 2017.
  • Dhull, S., & Narwal, M. S., “Prioritizing the Drivers of Green Supply Chain Management in Indian Manufacturing Industries Using Fuzzy TOPSIS Method: Government, Industry, Environment, and Public Perspectives”, Process Integration and Optimization for Sustainability, vol. 2, no. 1, pp. 47-60, 2018.
  • Boran, F. E., Genç, S., Kurt, M., and Akay, D., “A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method”, Expert Systems with Applications, vol. 36, no. 8, pp. 11363-11368, 2009.
  • Büyüközkan, G., and Güleryüz, S., “Lojistik Firma Web Sitelerinin Performanslarının Çok Kriterli Değerlendirilmesi”, Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi, vol. 31, no. 4, pp. 889-902, 2016.
  • Opricovic, S., “Multicriteria optimization of civil engineering systems”, Faculty of Civil Engineering, Belgrade, vol. 2, no. 1, pp. 5-21, 1998.
  • Opricovic, S., “Fuzzy VIKOR with an application to water resources planning”, Expert Systems with Applications, vol. 38, no. 10, pp. 12983-12990, 2011.
  • Shemshadi, A., Shirazi, H., Toreihi, M., and Tarokh, M. J., “A fuzzy VIKOR method for supplier selection based on entropy measure for objective weighting”, Expert Systems with Applications, vol. 38, no. 10, pp. 12160-12167, 2011.
  • Girubha, R. J., and Vinodh, S., “Application of fuzzy VIKOR and environmental impact analysis for material selection of an automotive component”, Materials & Design, vol. 37, pp. 478-486, 2012.
  • Vinodh, S., Varadharajan, A. R., and Subramanian, A., “Application of fuzzy VIKOR for concept selection in an agile environment”, The International Journal of Advanced Manufacturing Technology, vol. 65, no. 5-8, pp. 825-832, 2013.
  • Tadić, S., Zečević, S., and Krstić, M., “A novel hybrid MCDM model based on fuzzy DEMATEL, fuzzy ANP and fuzzy VIKOR for city logistics concept selection”, Expert Systems with Applications, vol. 41, no. 18, pp. 8112-8128, 2014.
  • Lee, G., Jun, K. S., and Chung, E. S., “Group decision-making approach for flood vulnerability identification using the fuzzy VIKOR method”, Natural Hazards and Earth System Sciences, vol. 15, no. 4, pp. 863-874, 2015.
  • Rostamzadeh, R., Govindan, K., Esmaeili, A., and Sabaghi, M., “Application of fuzzy VIKOR for evaluation of green supply chain management practices”, Ecological Indicators, vol. 49, pp. 188-203, 2015.
  • Liu, H. C., You, J. X., You, X. Y., and Shan, M. M., “A novel approach for failure mode and effects analysis using combination weighting and fuzzy VIKOR method”, Applied Soft Computing, vol. 28, pp. 579-588, 2015.
  • Chen, L. Y., and Wang, T. C., “Optimizing partners’ choice in IS/IT outsourcing projects: The strategic decision of fuzzy VIKOR”, International Journal of Production Economics, vol. 120, no. 1, pp. 233-242, 2009.
  • Kaya, T., and Kahraman, C., “Multicriteria renewable energy planning using an integrated fuzzy VIKOR & AHP methodology: The case of Istanbul”, Energy, vol. 35, no. 6, pp. 2517-2527, 2010.
  • Kim, Y., and Chung, E. S., “Fuzzy VIKOR approach for assessing the vulnerability of the water supply to climate change and variability in South Korea”, Applied Mathematical Modelling, vol. 37, no. 22, pp. 9419-9430, 2013.
  • Sdfghj Chang, T. H., “Fuzzy VIKOR method: a case study of the hospital service evaluation in Taiwan”, Information Sciences, vol. 271, pp. 196-212, 2014.
  • Safari, H., Faraji, Z., and Majidian, S., “Identifying and evaluating enterprise architecture risks using FMEA and fuzzy VIKOR”, Journal of Intelligent Manufacturing, vol. 27, no. 2, pp. 475-486, 2016.
  • Çelikbilek, Y., and Tüysüz, F., “A Fuzzy Multi Criteria Decision Making Approach for Evaluating Renewable Energy Sources”, The 4th International Fuzzy Systems Symposium – FUZZYSS’15, 5–6 Kasım 2015, İstanbul, Turkey, pp. 322-327, 2015.
  • Brauers, W. K., and Zavadskas, E. K., “The MOORA method and its application to privatization in a transition economy”, Control and Cybernetics, vol. 35, pp. 445-469, 2006.
  • Archana, M., and Sujatha, V., “Application of fuzzy moora and gra in multi-criterion decision making problems”, International Journal of Computer Applications, vol. 53, no. 9, pp. 46-50, 2012.
  • Mandal, U. K., and Sarkar, B., “Selection of best intelligent manufacturing system (ims) under fuzzy moora conflicting mcdm environment”, International Journal of Emerging Technology and Advanced Engineering, vol. 2, no. 9, pp. 301-310, 2012.
  • Baležentis, A., Baležentis, T., and Brauers, W. K., “Personnel selection based on computing with words and fuzzy MULTIMOORA”, Expert Systems with applications, vol. 39, no. 9, pp. 7961-7967, 2012.
  • Akkaya, G., Turanoğlu, B., and Öztaş, S., “An integrated fuzzy AHP and fuzzy MOORA approach to the problem of industrial engineering sector choosing”, Expert Systems with Applications, vol. 42, no. 24, pp. 9565-9573, 2015.
  • Matawale, C. R., Datta, S., and Mahapatra, S. S., “Supplier selection in agile supply chain: Application potential of FMLMCDM approach in comparison with Fuzzy-TOPSIS and Fuzzy-MOORA”, Benchmarking: An International Journal, vol. 23, no. 7, pp. 2027-2060, 2016.
  • Matawale, C. R., Datta, S., and Mahapatra, S. S., “Supplier selection in agile supply chain: Application potential of FMLMCDM approach in comparison with Fuzzy-TOPSIS and Fuzzy-MOORA”, Benchmarking: An International Journal, vol. 23, no. 7, pp. 2027-2060, 2016.
  • Karande, P., and Chakraborty, S., “A Fuzzy-MOORA approach for ERP system selection”, Decision Science Letters, vol. 1, no. 1, pp. 11-21, 2012.
  • Opricovic, S., and Tzeng, G. H., “Defuzzification within a multicriteria decision model”, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, vol. 11, no. 05, pp. 635-652, 2003.
Primary Language en
Subjects Industrial Engineering
Published Date April 2019
Journal Section Research Articles
Authors

Orcid: 0000-0003-0585-1085
Author: Yakup Çelikbilek (Primary Author)
Institution: İSTANBUL GELİŞİM ÜNİVERSİTESİ, İKTİSADİ, İDARİ VE SOSYAL BİLİMLER FAKÜLTESİ, YÖNETİM BİLİŞİM SİSTEMLERİ BÖLÜMÜ
Country: Turkey


Bibtex @research article { saufenbilder421856, journal = {Sakarya University Journal of Science}, issn = {1301-4048}, eissn = {2147-835X}, address = {Sakarya University}, year = {2019}, volume = {23}, pages = {139 - 148}, doi = {10.16984/saufenbilder.421856}, title = {The Importance of The Place of Defuzzification Step In Fuzzy Systems}, key = {cite}, author = {Çelikbilek, Yakup} }
APA Çelikbilek, Y . (2019). The Importance of The Place of Defuzzification Step In Fuzzy Systems. Sakarya University Journal of Science, 23 (2), 139-148. DOI: 10.16984/saufenbilder.421856
MLA Çelikbilek, Y . "The Importance of The Place of Defuzzification Step In Fuzzy Systems". Sakarya University Journal of Science 23 (2019): 139-148 <http://www.saujs.sakarya.edu.tr/issue/39539/421856>
Chicago Çelikbilek, Y . "The Importance of The Place of Defuzzification Step In Fuzzy Systems". Sakarya University Journal of Science 23 (2019): 139-148
RIS TY - JOUR T1 - The Importance of The Place of Defuzzification Step In Fuzzy Systems AU - Yakup Çelikbilek Y1 - 2019 PY - 2019 N1 - doi: 10.16984/saufenbilder.421856 DO - 10.16984/saufenbilder.421856 T2 - Sakarya University Journal of Science JF - Journal JO - JOR SP - 139 EP - 148 VL - 23 IS - 2 SN - 1301-4048-2147-835X M3 - doi: 10.16984/saufenbilder.421856 UR - https://doi.org/10.16984/saufenbilder.421856 Y2 - 2018 ER -
EndNote %0 Sakarya University Journal of Science The Importance of The Place of Defuzzification Step In Fuzzy Systems %A Yakup Çelikbilek %T The Importance of The Place of Defuzzification Step In Fuzzy Systems %D 2019 %J Sakarya University Journal of Science %P 1301-4048-2147-835X %V 23 %N 2 %R doi: 10.16984/saufenbilder.421856 %U 10.16984/saufenbilder.421856
ISNAD Çelikbilek, Yakup . "The Importance of The Place of Defuzzification Step In Fuzzy Systems". Sakarya University Journal of Science 23 / 2 (April 2019): 139-148. https://doi.org/10.16984/saufenbilder.421856