A hybrid ABC - Spherical Fuzzy AHP - ELECTRE group decision making method for stock management and an application.

Öz

In today's economic conditions, the reduction of inventory costs of enterprises is one of the important factors that lead to a decrease in production costs and increase in competitiveness. The aim of this study is to prevent stock deficits and surpluses that may occur by designing an applicable and effective raw material-stock management system. For this purpose, stock analyzes were made by using ABC, Spherical Fuzzy AHP and ELECTRE methods and an algorithm with four steps was proposed. In the first step, units were classified by using ABC analysis based on the unit price and demand quantities. In the second step, the Spherical Fuzzy AHP method was used. Here, criteria such as the availability of the product, substitutability, the delivery time of the order, and the effect of the product prices from currency fluctuations are discussed. These criteria have been evaluated together with business managers and engineers responsible for production and the criterion weights have been calculated with a group decision making approach. In the third step, by using the criterion weights in the ELECTRE method, the products are sorted and grouped according to this order. In the last step, the results obtained from ABC and SF-AHP - ELECTRE were combined and an evaluation scale was obtained. Within the scope of this study, an application of the proposed method for the furniture industry is included.

Anahtar Kelimeler

• Stock Management
• Spherical Fuzzy AHP
• Group Decision Making
• ELECTRE
• ABC
• MCDM

Stok yönetimi için ABC - Küresel Bulanık AHS - ELECTRE tabanlı melez grup karar verme yöntemi ve bir uygulama

Öz

Günümüz ekonomik koşullarında işletmelerin stok maliyetlerini azalmaları, üretim maliyetlerinin düşmesine ve rekabet gücünün artmasına yol açan önemli faktörlerden bir tanesidir. Bu çalışmanın amacı, uygulanabilir ve etkin bir hammadde-stok yönetim sistemi tasarlayarak oluşabilecek stok açıklarının ve fazlalıklarının önüne geçmektir. Bu amaç doğrultusunda ABC, Küresel Bulanık AHS ve ELECTRE yöntemleri beraber kullanılarak stok analizleri yapılmış ve dört adımdan oluşan yeni bir yöntem önerilmiştir. Birinci adımda ABC analizi kullanılmış, yıllık maliyet ve kullanım miktarlarına göre malzemeler sınıflandırılmıştır. İkinci adımda, Küresel Bulanık AHS metodu kullanılmıştır. Burada ürünün bulunabilirliği, ikame edilebilirliği, verilen siparişin ulaşma süresi ve malzeme fiyatlarının dalgalanmalardan etkilenmesi gibi kriterler ele alınmıştır. Bu kriterler işletme yöneticileri ve üretimden sorumlu mühendislerle beraber değerlendirilmiş ve grup karar verme yöntemi ile kriter ağırlıkları hesaplanmıştır. Üçüncü adımda, kriter ağırlıkları ELECTRE yönteminde kullanılarak ürünlerin sıralanması ve bu sıralamaya bağlı gruplanması sağlanmıştır. Son adımda ise ABC ve KB-AHS - ELECTRE’den elde edilen sonuçlar bir araya getirilmiş ve bir değerlendirme skalası elde oluşturulmuştur. Bu çalışma kapsamında önerilen yöntemin mobilya sektörü için bir uygulamasına yer verilmiştir.

Anahtar Kelimeler

• Stok Yönetimi
• Küresel Bulanık AHS
• Grup Karar Verme
• ELECTRE
• ABC
• MCDM

Kaynakça

1. Atanassov, K. T. (1986). Intuitionistic fuzzy sets. Fuzzy Sets and Systems, 20(1). https://doi.org/10.1016/S0165-0114(86)80034-3
2. Atanassov, K. T. (1989). More on intuitionistic fuzzy sets. Fuzzy Sets and Systems, 33(1). https://doi.org/10.1016/0165-0114(89)90215-7
3. Ayyildiz, E., & Taskin Gumus, A. (2020). 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. https://doi.org/10.1007/s11356-020-09640-0
4. Balaji, K., & Kumar, V. S. S. (2014). Multicriteria inventory ABC classification in an automobile rubber components manufacturing industry. In Procedia CIRP. https://doi.org/10.1016/j.procir.2014.02.044
5. Bernard, R. (1968). Classement Et Choix En Presence De Points De Vue Multiples (»). Revue Française d’informatique et de Recherche Opérationnelle.
6. Cakir, O., & Canbolat, M. S. (2008). A web-based decision support system for multi-criteria inventory classification using fuzzy AHP methodology. Expert Systems with Applications. https://doi.org/10.1016/j.eswa.2007.08.041
7. Figueira, J. R., Mousseau, V., & Roy, B. (2016). ELECTRE methods. International Series in Operations Research and Management Science. https://doi.org/10.1007/978-1-4939-3094-4_5
8. Garibaldi, J. M., & Ozen, T. (2007). Uncertain fuzzy reasoning: A case study in modelling expert decision making. IEEE Transactions on Fuzzy Systems, 15(1). https://doi.org/10.1109/TFUZZ.2006.889755

9. Gündoǧdu, F. K., & Kahraman, C. (2019). Spherical fuzzy sets and spherical fuzzy TOPSIS method. Journal of Intelligent and Fuzzy Systems. https://doi.org/10.3233/JIFS-181401
10. Gurnani, C. (2007). Economic analysis of inventory systems. International Journal of Production Research. https://doi.org/10.1080/00207548308942352
11. Hadi-Vencheh, A. (2010). An improvement to multiple criteria ABC inventory classification. European Journal of Operational Research. https://doi.org/10.1016/j.ejor.2009.04.013
12. Inderfurth, K. (1991). Safety stock optimization in multi-stage inventory systems. International Journal of Production Economics. https://doi.org/10.1016/0925-5273(91)90157-O
13. Kutlu Gündoğdu, F., & Kahraman, C. (2020a). A novel spherical fuzzy analytic hierarchy process and its renewable energy application. Soft Computing. https://doi.org/10.1007/s00500-019-04222-w
14. Kutlu Gündoğdu, F., & Kahraman, C. (2020b). Spherical fuzzy analytic hierarchy process (AHP) and its application to industrial robot selection. In Advances in Intelligent Systems and Computing. https://doi.org/10.1007/978-3-030-23756-1_117
15. Liu, J., Liao, X., Zhao, W., & Yang, N. (2016). A classification approach based on the outranking model for multiple criteria ABC analysis. Omega (United Kingdom). https://doi.org/10.1016/j.omega.2015.07.004
16. Lolli, F., Ishizaka, A., & Gamberini, R. (2014). New AHP-based approaches for multi-criteria inventory classification. International Journal of Production Economics. https://doi.org/10.1016/j.ijpe.2014.05.015
17. Michalski, G. (2009). Inventory management optimization as part of operational risk management. Economic Computation and Economic Cybernetics Studies and Research.
18. Minner, S. (1997). Dynamic programming algorithms for multi-stage safety stock optimization. OR Spectrum. https://doi.org/10.1007/BF01539783
19. Nahmias, S. (2004). Production and Operations Analysis. In Production and Operations Analysis.
20. Özdağoğlu, A. (2010). Analysis of Selection Criteria for Manufacturing Employees Using Fuzzy-AHP. Deü İşletme Fakültesi Dergisi, 9(1), 141–160. Retrieved from http://web.deu.edu.tr/dergi/index.php/isletme/article/view/18/0
21. Saaty, T. L. (1980). The Analytic Hierarchy Process. Education, 1–11. https://doi.org/10.3414/ME10-01-0028
22. Smarandache, F. (1999). A Unifying Field in Logics: Neutrosophic Logic, Neutrosophy, Neutrosophic Set, Neutrosophic Probability. American Research Press.
23. Torra, V. (2010). Hesitant fuzzy sets. International Journal of Intelligent Systems, 25(6). https://doi.org/10.1002/int.20418
24. Yager, R. R. (1986). On the theory of bags. International Journal of General Systems, 13(1). https://doi.org/10.1080/03081078608934952
25. Zadeh, L. A. (1975). The concept of a linguistic variable and its application to approximate reasoning-I. Information Sciences, 8(3), 199–249. https://doi.org/10.1016/0020-0255(75)90036-5
26. Zadeh, Lotfi A. (1965). Fuzzy Sets. Information and Control, 8, 338–353. https://doi.org/10.1109/2.53