Ambalaj Tedarikçi Seçim Probleminin Çözümü İçin Hibrit Çok Kriterli Bir Karar Verme Yöntemi Önerisi

Year 2021, Volume: 10 Issue: 2, 1118 - 1139, 30.06.2021

Özlem Karadağ Albayrak

https://doi.org/10.15869/itobiad.835506

Cited By: 1

Abstract

Tedarik zinciri boyunca seçim veya değerlendirme problemleri tedarikçileri farklı performans faktörlerine göre değerlendirerek ve birbirleriyle karşılaştırılmaları yapılarak çözülür. Bu şekilde tedarikçiler ile ilgili önemli ön bilgilerin elde edilmesini sağlanmış olur. İşletmeler rekabet güçlerini sürdürebilmek için tedarikçi seçimi için hızlı, etkin ve başarılı yöntemleri kullanmak isterler. Bu çalışma mal üretimi yapan bir işletmenin kendisine ambalaj malzemesi sağlayan/sağlamaya aday tedarikçiler içinde en uygun olanı seçmek için bir yöntem sunmuştur. Günümüz küresel rekabet ortamında, işletmeler piyasaya sundukları ürünleri için kullanacakları malzemelerin seçimine ilişkin kararları alınırken maliyetin azaltabilecek ve piyasada rekabet üstünlüğünü sağlayabilecek alternatifleri tercih ederler.
İnsan davranışından kaynaklanan görüş ayrılıkları nedeniyle karar süreçleri her zaman kesin bilgiler içermezler. Tedarikçi seçim problemleri çözülürken, karar vericilerin farklı görüşleri ve çıkar çatışmaları gibi birçok etken dikkate alınır. Çok Kriterli Karar Verme (ÇKKV) teknikleri, bu tür sorunlara çözüm bulma konusunda oldukça etkilidir. Bu makalenin amacı, bulanık bir ortamda bir imalat işletmesinin ambalaj tedarikçisi seçim sorununa bir çözüm sunmaktır. Bu amaçla sekiz tedarikçi 15 değerlendirme kriterine göre değerlendirilmiştir. Kararalma sürecinde 4 farklı karar vericinin görüşü başvurulmuştur. Sorunun çözümü, kriterlerin ağırlıklarını belirlemek için kullanılan Bulanık Analitik Hiyerarşi Süreci (F-AHP) ve alternatifler arasında tercih yapmak için kullanılan Ağırlıklı Birleşik Toplu Çarpım Değerlendirmesinden (F-WASPAS) oluşan karma bir modele dayanmaktadır. Kriterler ağırlıklarının belirlenmesine ilişkin yapılan analiz sonunda, en uygun tedarikçi seçimi problemleri analiz edilirken en çok etkili olan iki faktör sırası ile teslim tarihi ve fiyat olarak belirlenmiştir Yapılan değerlendirme sonucunda A2 en uygun tedarikçi olarak önerilmiştir. Sonuçların etkinliğini belirlemek için duyarlılık analizi yapılmıştır ve yine MARCOS, MABAC, SAW, ARAS, TOPSIS, EDAS yöntemleriyle elde edilen seçim sonuçlarına göre A2 en uygun tedarikçi olarak belirlenmiştir.          

Keywords

Bulanık Set, Tedarikçi Seçim Problemi, Çok Kriterli Karar Verme Teknikleri (ÇKKV), F-WASPAS, F-AHP.

A Hybrid Multi-Criteria Decision-Making Method Proposal For The Solution Of The Packaging Supplier Selection Problem

Abstract

Selection or evaluation problems are solved by looking at the different performance factors of the suppliers along the supply chain and by making comparisons with each other, and it is ensured that important preliminary information about the suppliers is obtained. This study has been prepared in order to choose the most suitable supplier among the suppliers that provide / are candidates to provide packaging material for an enterprise producing goods
Decision processes may not always have precision due to differences of opinion arising from human behaviour. When supplier selection problems are solved, many criteria, such as different opinions of decision-makers and their conflict of interests are considered. Multi-Criteria Decision Making (MCDM) techniques are highly effective in finding solutions to such problems. The goal of this article was to find a solution to packaging supplier selection problem of a manufacturing company in a fuzzy environment. To this end, eight suppliers were examined in line with 15 evaluation criteria. The opinions of 4 different decision-makers were taken during decision-making process. The solution of the problem was based upon a mixed model consisting of Fuzzy Analytic Hierarchy Process (F-AHP), used to determine the weights of the criteria, and Fuzzy Weighted Aggregated Sum Product Assessment (F-WASPAS), utilised to make preference among alternatives. At the end of the analysis on the determination of the criteria weights, the most appropriate supplier selection was determined as the delivery date and price, respectively, the two factors most influencing the construction phase. As a result of the evaluation made, A2 was specified to be the most proper supplier. Sensitivity analysis was performed to identify the effectiveness of the results. A2 was determined to be the most proper supplier according to the selection results obtained by MARCOS, MABAC, SAW, ARAS, TOPSIS, EDAS methods.          

Keywords

Fuzzy Set, Supplier Selection Problems, Multiple-criteria Decision-Making (MCDM), F-WASPAS, F-AHP.

References

• Ahmet, F., Kılıç K., Modification to Fuzzy Extent Analysis Method and its performans Analysis, 6th IESM Congerance Seville, Spain, 2015.
• Ayyildiz E., Gumus A.T., A novel spherical fuzzy AHP-integrated spherical WASPAS methodology for petrol station location selection problem: a real case study for İstanbul, Environmental Science and Pollution Research (2020) 27:36109–36120
• Bellman RE, Zadeh LA. Decision-making in a fuzzy environment management. Science, 1970;17(4):141–64.
• Chang, D-Y, Theory and Methodology, Applications of the extent analysis method on fuzzy AHP, European Journal of Operational Research (1996), 95; 649-655.
• Gumus, A.-T., Evaluation of hazardous waste transportation firms by using a two step fuzzy-AHP and TOPSIS methodology. Expert Systems with Applications, (2009), 36(2), 4067–4074
• Gögüs, Ö., Boucher T. O., Strong transitivity, rationality and weak monotonicity in fuzzy pairwise comparisons, Fuzzy Sets and Systems (1998), 94; 133 144.
• Hsieh, T.-Y., Lu, S.-T., & Tzeng, G.-H., Fuzzy MCDM approach for planning and design tenders selection in public office buildings. International Journal of Project Management, 2004, 22(7), 573–584.
• Hsu C-W., Hu A.H., Applying hazardous substance management to supplier selection using analytic network process, Journal of Cleaner Production 2009, 17; 255–264
• Jain N., Singh A. R., Upadhyay R. K., Sustainable supplier selection under attractive criteria through FIS and integrated fuzzy MCDM techniques, Internatıonal Journal Of Sustaınable Engıneerıng, DOI: 10.1080/19397038.2020.1737751.
• Kahraman, C., Cebeci, U. ve Da Ruan, “Multi-Attribute Comparison of Catering Service Companies Using Fuzzy AHP: The Case of Turkey”, International Journal of Production Economics, 2004, 87, 2, 171-184.
• Kaushik V. , Kumar A , Gupta H., Dixit G., A hybrid decision model for supplier selection in Online Fashion Retail (OFR), International Journal of Logistics Research and Applications, International Journal of Logistics Research and Applications, 2020, 4-25.
• Khan S. A., Kusi-Sarpong S., Arhin F. K., Kusi-Sarpong H., Supplier sustainability performance evaluation and selection: A framework and methodology, Journal of Cleaner Production 205 (2018) 964-979.
• Kuo R.,. Wang Y, Tien F., Integration of artificial neural network and MADA methods for green supplier selection, Journal of Cleaner Production, 2010, 18, 1161-1170
• Kulak, O. ve Kahraman, C., Fuzzy Multi-Attribute Selection Among Transportation Companies Using Axiomatic Design and Analytic Hierarchy Process, Information Sciences, 2005, 170, 2-4, 191-210.
• Liou, J.-J.-H., Yen, L., & Tzeng, G.-H., Building an effective safety management system for airlines. Journal of Air Transport Management, 2008, 14(1); 20–26.
• Ordoobadi S.M., Development of a supplier selection model using fuzzy logic, Supply Chain Management: An International Journal 2009, 14; 314–327.
• Ortiz‑Barrios M., Cabarcas‑Reyes J., Ishizaka A., Barbati M., Jaramillo‑Rueda N., Carrascal‑Zambrano G. J., A hybrid fuzzy multi‑criteria decision making model for selecting a sustainable supplier of forklift filters: a case study from the mining industry, Springer Science+Business Media, LLC, part of Springer Nature 2020.
• Öztürk, B. A., Özçelik F., Sustainable Supplier Selection with A Fuzzy Multi-Criteria Decision Making Method Based on Triple Bottom Line, Business and Economics Research Journal, 2004, 5(3), 129-147.
• Prajapati H., Kant R., Tripathi S. M., An integrated framework for prioritizing the outsourcing performance outcomes, Journal of Global Operations and Strategic Sourcing, DOI 10.1108/JGOSS-06-2019-00
• Petrović G., Mihajlović J., Ćojbašić Z., MadićM., Marinković D., Comparıson Of Three Fuzzy Mcdm Methods For Solvıng The Supplıer Selectıon Problem, Facta Universitatis Series Mechanical Engineering, 2019, 17(3):455-469.
• Saaty T. L., The analytic hierarchy process. New York, USA: McGraw-Hill, 1980
• Shen, L., Olfat, L., Govindan, K., Khodaverdi, R., & Diabat, A., A fuzzy multi criteria approach for evaluating green supplier’s performance in green supply chain with linguistic preferences. Resources, Conservation and Recycling, 2013, 74: 170–179.
• Sadoughi, S., Yarahmadi, R., Taghdisi, M. H., Mehrabi, M. (2012), Evaluating and prioritizing of performance indicators of health, safety, and environment using fuzzy TOPSIS, African Journal of Business Management, 6 (5), 2026-2033.
• Singh R. K., Modgil S., Supplier selection using SWARA and WASPAS – a case study of Indian cement industry, Measurıng Busıness Excellence, 2020, 24(2), 243-265.
• Sun C-C., A performance evaluation model by integrating fuzzy AHP and fuzzy TOPSIS methods, Expert Systems with Applications 2010, 37: 7745–7754.
• Sen D. P., Datta S., Mahapatra S.S., Sustainable supplier selection in intuitionistic fuzzy environment: a decision-making perspective, Benchmarking: An International Journal, 2018, 25(2), 545-557.
• Szmıdt, E., Kacprzyk J., Using intuitionistic fuzzy sets m group decision making, Control and Cybernetics, 2002, 31(4), 1037-1053.
• Stevic Z., , Pamucar D., Puska A., Chatterjee P., Sustainable supplier selection in healthcare industries using a new MCDM method: Measurement Alternatives and Ranking according to Compromise Solution (MARCOS), Computers & Industrial Engineering, 2020, 140, (2019), 10623.
• Tolga, E., Demircan, M. L. ve Kahraman, C., “Operating System Selection Using Fuzzy Replacement Analysis and Analytic Hierarchy Process”, International Journal of Production Economic, 2005, 97, 1, 89-117
• Turskis, Z.; Zavadskas, E. K.; Antucheviciene, J.; Kosareva, N., A hybrid model based on fuzzy AHP and fuzzyWASPAS for construction site selection, International Journal of Computers Communications & Control, 2015, 10(6), 113-128.
• Tseng M.L., Chiu A.S., Evaluating firm’s green supply chain management in linguistic preferences, Journal of Cleaner Production, 2013, 40; 22-31.
• Zhu Q., Dou Y., Sarkis J., A portfolio-based analysis for green supplier management using the analytical network process, Supply Chain Management: An International Journal, 2010, 15; 306–319.
• Xiong L., Zhong S., Liu S. , Zhang X., Li Y., An Approach for Resilient-Green Supplier Selection Based on WASPAS, BWM, and TOPSIS under Intuitionistic Fuzzy Sets, Hindawi Mathematical Problems in Engineering ,2020, 1-18, DOI: 10.1155/2020/1761893.
• Wu, W.-W., & Lee, Y.-T., Developing global managers’ competencies using the fuzzy DEMATEL method. Expert Systems with Applications, 2007; 32(2): 499–507.
• Yucesan M , Mete S. , Serin F., Celik E., Gul M., An Integrated Best-Worst and Interval Type-2 Fuzzy TOPSIS Methodology for Green Supplier Selection, Mathematics 2019, 7, 182; 2-19.
• Zimmermann, H. J., Fuzzy Set Theory-and Its Applications, Fourth Edition. New York: Springer Science+Business Media., 2001
• Zadeh, Z.A.,, “Fuzzy sets”, Information and Control, 1965, 2 (3): 338–353.
• Zavadskas E. K., Turskis Z., Antucheviciene J., Zakarevicius A., Optimization of weighted aggregated sum product assessment, Elektron Elektrotech, 2012; 122, pp. 3–6, 2012.