Hibritlenmiş Fuzzy-AHP ve TOPSIS Yöntemi İle Ürün Seçimi için Bir Karar Destek Sistemi

KUŞAKCI ,Ali Osman

Ali Osman KUŞAKCI

(İbn Haldun Üniversitesi, Yönetim Bilimleri Fakültesi, İşletme Bölümü, İstanbul, Türkiye)

Uluslararası Mühendislik Araştırma ve Geliştirme Dergisi

Yıl: 2019Cilt: 11Sayı: 1ISSN: 1308-5514 / 1308-5514Sayfa Aralığı: 99 - 108Metin Dili: Türkçe

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Türkçe
İngilizce

Hibritlenmiş Fuzzy-AHP ve TOPSIS Yöntemi İle Ürün Seçimi için Bir Karar Destek Sistemi

Öz: Ürün gamının çok geniş olduğu ürün aileleleri için talep edilen ürünün müşterinin isteği doğrultusunda; maliyet, kalite,fonksiyonellik gibi müşterinin ihtiyaçlarına/önceliklerine en iyi cevap verebilecek şekilde seçilmesi süreci karmaşık ve zahmetlibir Çok Kriterli Karar Verme (ÇKKV) problemidir. Bu çalışmada, Bulanık-AHP ve TOPSIS metotlarını kullanarak endüstriyeltip fan seçimi problemi için hibrit bir karar destek sistemi önerilmektedir. Önerilen model ile müşterinin taleplerine veönceliklerine göre kriter ağırlıklarının Bulanık-AHP ile tespiti yapılmaktadır. Elde edilen kriter ağırlıkları kullanılarak TOPSISyöntemi ile en iyi alternatifler sıralanmakta ve müşteriye sunulmaktadır

Anahtar Kelimeler:

Konu Alanı:

A Decision Support System for Product Selection Using Hybridized Fuzzy-AHP TOPSIS Methods

Öz:Product selection process requires perfect satisfaction of the customer needs and preferences in terms of quality, cost and functionality. Considering this aspects, it is a complex multi-criteria decision making problem. This statement is especially true for such product families with wide product variety. This study aims to design an interactive decison support tool for selecting industrial fans by employing a hybridized fuzzy-AHP and TOPSIS approach. With this work, an expert system for industrial fan selection is realized which collects customer’s requirements and preferences with Fuzzy-AHP and ranks the best fitting alternative products using TOPSIS approach.

Anahtar Kelimeler:

Konu Alanı:

Belge Türü: DergiMakale Türü: Araştırma MakalesiErişim Formatı: Erişime Açık

Abdullah, L., & Zulkifli, N. (2015). Integration of fuzzy AHP and interval type-2 fuzzy DEMATEL: An application to human resource management. Expert Systems with Applications, 42(9), 4397–4409. https://doi.org/10.1016/j.eswa.2015.01.021
Ahmed Ali, B. A., Sapuan, S. M., Zainudin, E. S., & Othman, M. (2015). Implementation of the expert decision system for environmental assessment in composite materials selection for automotive components. Journal of Cleaner Production, 107, 557–567. https://doi.org/10.1016/j.jclepro.2015.05.084
Al-Oqla, F. M., & Salit, M. S. (2017). Material selection of natural fiber composites using the analytical hierarchy process. In Materials Selection for Natural Fiber Composites (pp. 169–234). Elsevier. https://doi.org/10.1016/B978-0-08-100958-1.00006-2
Aydin, N., Celik, E., & Gumus, A. T. (2015). A hierarchical customer satisfaction framework for evaluating rail transit systems of Istanbul. Transportation Research Part A: Policy and Practice, 77, 61–81. https://doi.org/10.1016/j.tra.2015.03.029
Ayhan, M. B. (2013). A Fuzzy AHP Approach for Supplier Selection Problem: A Case Study in a Gearmotor Company. Internation Journal of Managing Value and Supply Chains (IJMVSC), 4(3), 11–23. https://doi.org/10.5121/ijmvsc.2013.4302
Ayvaz, B., & Kuşakcı, A. O. (2017). A trapezoidal type-2 fuzzy multi-criteria decision making method based on TOPSIS for supplier selection. Pamukkale University Journal of Engineering Sciences, 23(1), 71–80. https://doi.org/10.5505/pajes.2016.56563
Balo, F., & Şağbanşua, L. (2016). The Selection of the Best Solar Panel for the Photovoltaic System Design by Using AHP. Energy Procedia, 100, 50–53. https://doi.org/10.1016/j.egypro.2016.10.151
Baykal, N., & Beyan, T. (2004). Bulanık Mantık İlke Ve Temelleri (1st ed.). İstanbul: Seçkin.
Behzadian, M., Khanmohammadi Otaghsara, S., Yazdani, M., & Ignatius, J. (2012). A state-of the-art survey of TOPSIS applications. Expert Systems with Applications, 39(17), 13051–13069. https://doi.org/10.1016/j.eswa.2012.05.056
Buckley, J. J. (1985). Ranking alternatives using fuzzy numbers. Fuzzy Sets and Systems, 15(1), 21–31. https://doi.org/10.1016/0165-0114(85)90013-2
Bulut, E., Duru, O., & Kocak, G. (2015). Rotational priority investigation in fuzzy analytic hierarchy process design: An empirical study on the marine engine selection problem. Applied Mathematical Modelling, 39(2), 913–923. https://doi.org/10.1016/j.apm.2014.07.018
Caputo, A. C., Pelagagge, P. M., & Salini, P. (2013). AHP-based methodology for selecting safety devices of industrial machinery. Safety Science, 53, 202–218. https://doi.org/10.1016/j.ssci.2012.10.006
Celik, E., Gul, M., Aydin, N., Gumus, A. T., & Guneri, A. F. (2015). A comprehensive review of multi criteria decision making approaches based on interval type-2 fuzzy sets. Knowledge-Based Systems, 85, 329–341. https://doi.org/10.1016/j.knosys.2015.06.004
Dožić, S., & Kalić, M. (2015). Comparison of Two MCDM Methodologies in Aircraft Type Selection Problem. Transportation Research Procedia, 10, 910–919. https://doi.org/10.1016/j.trpro.2015.09.044
Durán, O., & Aguilo, J. (2008). Computer-aided machine-tool selection based on a Fuzzy-AHP approach. Expert Systems with Applications, 34(3), 1787–1794. https://doi.org/10.1016/j.eswa.2007.01.046
Erdoğan, M., & Kaya, İ. (2016). Evaluating Alternative-Fuel Busses for Public Transportation in Istanbul Using Interval Type2 Fuzzy AHP and TOPSIS. Journal of Multiple-Valued Logic & Soft Computing, 26(6), 625. Retrieved from http://ezproxy.ticaret.edu.tr/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=edb&AN=116399297&site=eds -live
Görener, A., Ayvaz, B., Kusakci, A. O., & Altinok, E. (2017). A hybrid type-2 fuzzy based supplier performance evaluation methodology : The Turkish Airlines technic case. Applied Soft Computing, 56(1), 436–445. https://doi.org/10.1016/j.asoc.2017.03.026
Gul, M., Celik, E., Gumus, A. T., & Guneri, A. F. (2017). A fuzzy logic based PROMETHEE method for material selection problems. Beni-Suef University Journal of Basic and Applied Sciences. https://doi.org/10.1016/j.bjbas.2017.07.002
Kilic, H. S., Zaim, S., & Delen, D. (2014). Development of a hybrid methodology for ERP system selection: The case of Turkish Airlines. Decision Support Systems, 66, 82–92. https://doi.org/10.1016/j.dss.2014.06.011
Krohling, R. A., & Pacheco, A. G. C. (2015). A-TOPSIS – An Approach Based on TOPSIS for Ranking Evolutionary Algorithms. Procedia Computer Science, 55(1), 308–317. https://doi.org/10.1016/j.procs.2015.07.054
Lai, Y.-J., Liu, T.-Y., & Hwang, C.-L. (1994). TOPSIS for MODM. European Journal of Operational Research, 76(3), 486–500. https://doi.org/10.1016/0377-2217(94)90282-8
Mardani, A., Jusoh, A., & Zavadskas, E. K. (2015). Fuzzy multiple criteria decision-making techniques and applications - Two decades review from 1994 to 2014. Expert Systems with Applications, 42(8), 4126–4148. https://doi.org/10.1016/j.eswa.2015.01.003
Meng, K., Lou, P., Peng, X., & Prybutok, V. (2016). A hybrid approach for performance evaluation and optimized selection of recoverable end-of-life products in the reverse supply chain. Computers & Industrial Engineering, 98, 171–184. https://doi.org/10.1016/j.cie.2016.05.025
Özbek, A. (2014). Selection of Executives in Non-Governmental Organizations with an Integrated Approach. Uluslararası Muhendislik Arastirma ve Gelistirme Dergisi, 6(2), 39–46. https://doi.org/10.29137/umagd.346092
Scott, J., Ho, W., Dey, P. K., & Talluri, S. (2015). A decision support system for supplier selection and order allocation in stochastic, multi-stakeholder and multi-criteria environments. International Journal of Production Economics, 166, 226–237. https://doi.org/10.1016/j.ijpe.2014.11.008
Serrai, W., Abdelli, A., Mokdad, L., & Hammal, Y. (2017). Towards an efficient and a more accurate web service selection using MCDM methods. Journal of Computational Science. https://doi.org/10.1016/j.jocs.2017.05.024
Uzun, S., & Kuşakcı, A. O. (2016). AFET LOJİSTİĞİ ALANINDA TESİS YERİ SEÇİMİ ÇALIŞMALARI. In International Symposium on Natural Hazards and Hazard Management 2016 (pp. 798–806). Karabük.
Yurdakul, M. (2004). AHP as a strategic decision-making tool to justify machine tool selection. Journal of Materials Processing Technology, 146(3), 365–376. https://doi.org/10.1016/j.jmatprotec.2003.11.026