HİBRİT BULANIK BİR ORTAMDA MOBİLYA ÜRETİM TESİSİ KURULUŞ YERİ SEÇİMİNDE AHP VE GRA KOMBİNASYONU

Year 2024, Volume: 8 Issue: 2, 147 - 162, 31.10.2024

Abdullah Cemil İlçe , Hasan Hüseyin Ciritcioğlu , Tuğba Tunacan

https://doi.org/10.32328/turkjforsci.1521382

Abstract

Bu çalışma yeni kurulan bir mobilya tesisinin yer seçimi problemini çözmeyi amaçlamaktadır. Yer seçimi, işletmelerin yaşam döngüleri boyunca faaliyetlerini sürdürmek için katlanmaları gereken maliyetlerle doğrudan ilgilidir. Bu nedenle işletmelerin kuruluş yeri oldukça kritik öneme sahiptir. Çalışmada bulanık analitik hiyerarşi süreci (B-AHS) ve bulanık gri ilişki analizi (B-GRA) ile bütünleşik bir yöntem önerilmektedir. B-GRA alternatifleri sıralamak için kullanılırken, kriterlerin öncelik ağırlıkları B-AHP ile tahmin edilmektedir. Çok kriterli karar verme yöntemlerinin kullanımı sadece maliyet optimizasyonu için değil, aynı zamanda işletmelerin sürdürülebilirliğini sağlamak için birçok parametrenin (teknik, sosyal, ekonomik, demografik vb.) eş zamanlı olarak optimizasyonuna yöneliktir. Bu problemde göz önünde bulundurulan ana faktörler yakınlık, çevre, altyapı ve ekonomi olup Türkiye'deki şehirlerden Antalya, Düzce, Gaziantep, Kayseri ve Kocaeli aday lokasyonlar olarak seçilmiştir. Birleştirilmiş yöntemin uygulama adımları tanımlanmış ve örnek problemin sonucu sunulmuştur.

Keywords

B-AHP, B-GRA, tesis kuruluş yeri seçimi, çok kriterli karar verme yöntemi, sürdürülebilirlik

A COMBINATION OF AHP AND GRA FOR FURNITURE MANUFACTURING FACILITY LOCATION SELECTION IN A HYBRID FUZZY ENVIRONMENT

Abstract

This paper aims to solve the location selection problem for a newly established furniture facility. The choice of location is directly related to the costs businesses should bear to continue their operations throughout their life cycle. Therefore, the location of the establishment is very critical for enterprises. For this problem, we propose a combined method with fuzzy analytic hierarchy process (F AHP) and fuzzy grey relation analysis (F-GRA). F-GRA is used to rank the alternatives, while the priority weights of the criteria are estimated via F-AHP. The use of multi-criteria decision-making methods is not only for cost optimization but also optimization of many parameters (technical, social, economic, demographic, etc.) simultaneously to ensure the sustainability of enterprises. In this problem, the main factors considered are closeness, environment, infrastructure, and economy, and the candidate locations are selected as Antalya, Duzce, Gaziantep, Kayseri, Kocaeli, cities in Turkey. The application steps of the combined method are defined, and the result of the case problem is represented.

Keywords

B-AHP, B-GRA, facility location selection, multi-criteria decision making methods, sustainability

Ethical Statement

This study does not require any ethics committee approval.

Supporting Institution

The study received no financial support.

References

• Agrebi, M., Abed, M., & Omri, M. N. (2017). ELECTRE I Based Relevance Decision‐Makers Feedback to the Location Selection of Distribution Centers. Journal of Advanced Transportation, 2017(1), 7131094.
• Al-Hawari, T., Mumani, A., & Momani, A. (2014). Application of the Analytic Network Process to facility layout selection. Journal of manufacturing systems, 33(4), 488-497.
• Beskese, A., Demir, H. H., Ozcan, H. K., & Okten, H. E. (2015). Landfill site selection using fuzzy AHP and fuzzy TOPSIS: a case study for Istanbul. Environmental Earth Sciences, 73, 3513-3521.
• Boran, F. E. (2011). An integrated intuitionistic fuzzy multi criteria decision making method for facility location selection. Mathematical and Computational Applications, 16(2), 487-496.
• Buckley, J. J. (1985). Fuzzy hierarchical analysis. Fuzzy sets and systems, 17(3), 233-247.
• Burdurlu, E., & Ejder, E. (2003). Location choice for furniture industry firms by using Analytic Hierarchy Process (AHP) method. Gazi University Journal of Science, 16(2), 369-373.
• Chou, S. Y., Chang, Y. H., & Shen, C. Y. (2008). A fuzzy simple additive weighting system under group decision-making for facility location selection with objective/subjective attributes. European Journal of Operational Research, 189(1), 132-145.
• Dağdeviren, M., Eren, T.(2001). Using analytical hierarchy process and 0-1 target programming methods in supplier selection (In Turkish). Journal of the Faculty of Engineering and Architecture of Gazi University. 16(1), 41-52.
• Dağdeviren, M. (2007). Personnel selection with fuzzy analytical hierarchy process and an application. Journal of the Faculty of Engineering and Architecture of Gazi University, 22(4), 791-799.
• Erdoğan, M., & Kaya, I. (2016). A combined fuzzy approach to determine the best region for a nuclear power plant in Turkey. Applied Soft Computing, 39, 84-93.
• Ertuğrul, İ. (2011). Fuzzy group decision making for the selection of facility location. Group Decision and Negotiation, 20, 725-740.
• 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.
• Giresunlu, M., Tanritanir, E., Öztürk, T.A.(1998) AHP method selection in the MDF industry (In Turkish). In: 75th Anniversary of the Republic of Turkey Symposium on Forestry. pp. 612–618.
• Göksu, A., Güngör, İ. (2008). Fuzzy analytic hierarchical process and implementation of university preference ranking. (In Tukish). Süleyman Demirel Univ. Journal of Faculty of Economics and Administrative. Science. 13, 1–26.
• Gupta, P., Mehlawat, M. K., & Grover, N. (2016). Intuitionistic fuzzy multi-attribute group decision-making with an application to plant location selection based on a new extended VIKOR method. Information Sciences, 370, 184-203.
• Gumus, A. T. (2009). Evaluation of hazardous waste transportation firms by using a two step fuzzy-AHP and TOPSIS methodology. Expert systems with applications, 36(2), 4067-4074.
• Hanine, M., Boutkhoum, O., Tikniouine, A., & Agouti, T. (2016). Comparison of fuzzy AHP and fuzzy TODIM methods for landfill location selection. Springer Plus, 5, 1-30.
• Hsu, C. I., & Wen, Y. H. (2000). Application of grey theory and multiobjective programming towards airline network design. European Journal of Operational Research, 127(1), 44-68.
• İmren, E. (2011) Selection of establishment place using analytical hierarchy method in furniture industry (In Turkish), Msc. Thesis,p.105.
• Ju-Long, D. (1982). Control problems of grey systems. Systems & control letters, 1(5), 288-294.
• Kabak, M., Javadi, H., Aktas, A., & Ecer, B. (2022). GIS-Based Multi-Criteria Decision Making for Site Selection: An Application of GRP Pipe Production Plant. Journal of Multiple-Valued Logic & Soft Computing, 39,1-23.
• Kahraman, C., Ruan, D., & Doǧan, I. (2003). Fuzzy group decision-making for facility location selection. Information sciences, 157, 135-153.
• Kharat, M. G., Kamble, S. J., Raut, R. D., Kamble, S. S., & Dhume, S. M. (2016). Modeling landfill site selection using an integrated fuzzy MCDM approach. Modeling Earth Systems and Environment, 2, 1-16.
• Kuo, R. J., Chi, S. C., & Kao, S. S. (1999). A decision support system for locating convenience store through fuzzy AHP. Computers & Industrial Engineering, 37(1-2), 323-326.
• Liu, S., & Forrest, J. Y. L. (2010). Grey systems: theory and applications. Springer Science & Business Media. Mahmoodzadeh, S., Shahrabi, J., Pariazar, M., & Zaeri, M. S. (2007). Project selection by using fuzzy AHP and TOPSIS technique. International Journal of Industrial and Manufacturing Engineering, 1(6), 270-275.
• Popovic, G., Stanujkic, D., Brzakovic, M., & Karabasevic, D. (2019). A multiple-criteria decision-making model for the selection of a hotel location. Land use policy, 84, 49-58.
• Özdağoğlu, A. (2012). A multi-criteria decision-making methodology on the selection of facility location: fuzzy ANP. The International Journal of Advanced Manufacturing Technology, 59, 787-803.
• Özel, H.B., Karayılmazlar, S., Demirci, A.(2014) Location selection for forestation studies using Mediterranean pine species (Pinus brutia Ten. and Pinus pinea L.) with the analytical hierarchy process (AHP) method in Bartın Basin (In Turkish). National Mediterr. For. Environ. Symp. Futur. Mediterr. For. Sustain. Soc. Environ. 22–24
• Saaty, T.L. (1980) The Analytic Hierarchy Process. McGraw-Hill, New York.
• Saaty, T. L. (1990). How to make a decision: the analytic hierarchy process. European journal of operational research, 48(1), 9-26.
• Safari, H., Faghih, A., & Fathi, M. R. (2012). Fuzzy multi-criteria decision making method for facility location selection. African Journal of Business Management, 6(1), 206-212.
• Selcuk, L. (2013) An avalanche hazard model for Bitlis Province, Turkey, using GIS based multicriteria decision analysis, Turkish Journal of Earth Sciences, 22: 523–535
• Singh, R. K. (2016). Facility location selection using extent fuzzy AHP. Int. Advanced Research J. in Science, Engineering and Technology, 3(2).
• Şahin, T., Ocak, S., & Top, M. (2019). Analytic hierarchy process for hospital site selection. Health Policy and Technology, 8(1), 42-50.
• Şen, H., & Demiral, M. F. (2016). Hospital Location Selection with Grey System Theory. European Journal of Economics and Business Studies, Articles, 2(2), 66-79.
• Van Laarhoven, P.J.M. & Pedrycz, W.(1983). A fuzzy extension of Saaty's priority theory. Fuzzy sets Systems. 11(1-3), 229–241.
• Vijay, M. A., & Shankar, C. (2010). Facility Location Selection using PROMETHEE II Method. In Proceedings of the 2010 International Conference on Industrial Engineering and Operations Management, Dhaka, Bangladesh (pp. 9-10)
• Wichapa, N., & Khokhajaikiat, P. (2017). Solving multi-objective facility location problem using the fuzzy analytical hierarchy process and goal programming: a case study on infectious waste disposal centers. Operations Research Perspectives, 4, 39-48.
• Yaşlıoğlu, M. M., & Önder, E. (2016). Solving facility location problem for a plastic goods manufacturing company in Turkey using AHP and TOPSIS methods. Yönetim Bilimleri Dergisi, 14(28), 223-249.
• Yong, D. (2006). Plant location selection based on fuzzy TOPSIS. The International Journal of Advanced Manufacturing Technology, 28, 839-844.