Lojistik Merkezi Yer Seçimi için Aralık Değerli Sezgisel Bulanık Sayılara Dayalı Genişletilmiş VIKOR Yöntemi

Yıl 2022, , 1821 - 1837, 30.09.2022

Rahmi Baki

https://doi.org/10.15869/itobiad.1084212

Cited By: 1

Öz

Lojistik merkezler (LM) için uygun yerin belirlenmesi, rekabet avantajı elde etmenin, sürdürmenin ve tedarik zinciri faaliyetlerinin verimliliğini artırmanın anahtarıdır. Artan müşteri beklentileri, lojistik maliyetlerinin azaltılmasına yönelik çabalar ve lojistik sektöründe yaşanan rekabet yoğunluğu son yıllarda birçok yeni LM kurulmasına neden olmuştur. Bu merkezler yük taşımacılığında verimliliğin artmasına, lojistik hizmetlerin optimize edilmesine ve bulundukları kentteki trafiğin azaltılmasında önemli ölçüde katkı sağlamaktadır. LM'lerin artan önemi ve konumlarının lojistik faaliyetler üzerindeki önemli etkisi, kurulum yeri seçimini stratejik bir değerlendirme haline getirmiştir. Ancak, LM konum alternatiflerini değerlendirmek, birçok faktörün hesaba katılması gereken karmaşık bir süreçtir. Bu çalışmanın amacı, aralık değerli sezgisel bulanık sayılara (ADSBS) dayalı genişletilmiş bir VlseKriterijuska Optimizacija I Komoromisno Resenje (VIKOR) yaklaşımı önermek ve uygulanabilirliğini test etmektir. ADSBS'ın uygulanması, insan düşünce ve karar süreçlerindeki belirsizlikle başa çıkmaya katkıda bulunur. Öte yandan VIKOR birbiriyle çelişen ve farklı birimler tarafından temsil edilen kriterleri sıralamayı kolaylaştıran ve uzlaşmacı bir çözüm sunan bir karar verme tekniğidir. Bu çalışmada önerilen ADSBS aracılığıyla genişletilmiş VIKOR yaklaşımının uygulanabilirliği, LM konum alternatiflerinin değerlendirildiği sayısal bir örnekte test edilmiştir. Kriter ağırlıklarının belirlenmesi ve alternatiflerin sıralanması için üç uzman karar vericiye danışılmıştır. Karar vericiler, lojistik ve planlama uzmanı, lojistik operasyon yöneticisi ve tedarik zinciri başmühendisi olarak görev yapmaktadır. Uygulamada alternatifler altı kriter (altyapı, müşteriye yakınlık, tedarikçilere yakınlık, intermodal bağlantı, işgücü arzı ve güvenlik/güvenirlilik) dikkate alınarak değerlendirilmiştir. Sonuç olarak kriterler ağırlıklarına göre intermodal bağlantı (0,255), altyapı (0,194), güvenlik/güvenlik (0,169), müşterilere yakınlık (0,158), tedarikçilere yakınlık (0,131) ve iş gücü arzı (0,093) biçiminde sıralanmıştır. Çalışmada elde edilen bulguların araştırmacılara ve sektör yöneticilerine katkı sağlaması beklenmektedir.

Anahtar Kelimeler

Bulanık Küme, Aralık Değerli Sezgisel Bulanık Sayılar, VIKOR, Lojistik Merkez, Yer Seçimi

Extended VIKOR Method based on Interval-Valued Intuitionistic Fuzzy Numbers for Selection of Logistics Centre Location

Öz

Identifying the appropriate location for logistics centres (LC) is key to gaining and maintaining a competitive advantage and increasing the efficiency of supply chain activities. Increasing customer expectations, efforts to reduce logistics costs and the intensity of competition in the logistics sector have led to the establishment of many new LMs in recent years. These centers contribute significantly to increasing efficiency in freight transportation, optimizing logistics services and reducing the traffic. The increasing importance of LCs and the significant impact of their location on logistics activities have made the choice of installation site a strategic consideration. However, evaluating LC location alternatives is a complex process that must take many factors into account. The aim of the present study is to propose an extended VlseKriterijuska Optimizacija I Komoromisno Resenje (VIKOR) approach based on interval-valued intuitionistic fuzzy numbers (IVIFN) and test its feasibility. Applying IVIFN contributes to coping with uncertainty in human thought and decision processes. On the other hand, VIKOR is a decision-making technique that facilitates ranking criteria that are contradictory and represented by different units, and it offers a compromise solution. The feasibility of the extended VIKOR approach through IVIFN proposed in this study was tested in a numerical example in which LC location alternatives were evaluated. Three experts were consulted to determine the criterion weights and to rank the alternatives. Decision makers serve as logistics and planning specialist, logistics operations manager and supply chain chief engineer. In practice, alternatives were evaluated by considering six criteria. As a result, criteria are listed in the form of intermodal connection (0.255), infrastructure (0.194), security/safety (0.169), proximity to customers (0.158), proximity to suppliers (0.131), and labour supply (0.093), according to their weighted importance. It is expected that the findings obtained in the study will contribute to researchers and sector managers.

Anahtar Kelimeler

Fuzzy Set, Interval-Valued Intuitionistic Fuzzy Numbers, VIKOR, Logistics Centre, Location Selection

Kaynakça

• Atanassov, K. (2016). Intuitionistic fuzzy sets. International Journal Bioautomation, 20(S1), 1-6.
• Awasthi, A., Chauhan, S. S., & Goyal, S. K. (2011). A multi-criteria decision making approach for location planning for urban distribution centers under uncertainty. Mathematical and Computer Modelling, 53(1-2), 98-109.
• Büyüközkan, G., Göçer, F., & Feyzioğlu, O. (2018). Cloud computing technology selection based on interval-valued intuitionistic fuzzy MCDM methods. Soft Computing, 22(15), 5091-5114.
• Dammak, F., Baccour, L., & Alimi, A. M. (2020). A new ranking method for TOPSIS and VIKOR under interval valued intuitionistic fuzzy sets and possibility measures. Journal of Intelligent & Fuzzy Systems, 38(4), 4459-4469.
• Deng, H., & Yeh, C. H. (2006). Simulation-based evaluation of defuzzification-based approaches to fuzzy multiattribute decision making. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, 36(5), 968-977.
• Dey, B., Bairagi, B., Sarkar, B., & Sanyal, S. K. (2016). Warehouse location selection by fuzzy multi-criteria decision making methodologies based on subjective and objective criteria. International Journal of Management Science and Engineering Management, 11(4), 262-278.
• Dyck, V. G. K., & Ismael, H. M. (2015). Multi-criteria evaluation of port competitiveness in West Africa using analytic hierarchy process (AHP). American Journal of Industrial and Business Management, 5(06), 432.
• Elevli, B. (2014). Logistics freight center locations decision by using Fuzzy-PROMETHEE. Transport, 29(4), 412-418.
• Essaadi, I., Grabot, B., & Féniès, P. (2019). Location of global logistic hubs within Africa based on a fuzzy multi-criteria approach. Computers & Industrial Engineering, 132, 1-22.
• Grine, F. Z., Kamach, O., & Sefiani, N. (2018, July). Developing a Multi-Criteria Decision Making Model for identifying factors influencing the location of logistic hubs: A case study of Morocco. In Proceedings of the International Conference on Industrial Engineering and Operations Management Paris, France, 32178-3225.
• Kayikci, Y. (2010). A conceptual model for intermodal freight logistics centre location decisions. Procedia-Social and Behavioral Sciences, 2(3), 6297-6311.
• Li, C., & Jiang, H. (2011, August). Extension of VIKOR method with interval-valued intuitionistic fuzzy sets. In 2011 International Conference on Management and Service Science (pp. 1-4). IEEE.
• Lirn, T. C., Thanopoulou, H. A., Beynon, M. J., & Beresford, A. K. C. (2004). An application of AHP on transhipment port selection: a global perspective. Maritime Economics & Logistics, 6(1), 70-91.
• Long, S., & Grasman, S. E. (2012). A strategic decision model for evaluating inland freight hub locations. Research in Transportation Business & Management, 5, 92-98.
• Narayanamoorthy, S., Geetha, S., Rakkiyappan, R., & Joo, Y. H. (2019). Interval-valued intuitionistic hesitant fuzzy entropy based VIKOR method for industrial robots selection. Expert Systems with Applications, 121, 28-37.
• Onder, E., & Yıldırım, B. F. (2014). VIKOR method for ranking logistic villages in Turkey. Journal of Management and Economics Research, 12(23), 293-314.
• Opricovic, S., & Tzeng, G. H. (2002). Multicriteria planning of post‐earthquake sustainable reconstruction. Computer‐Aided Civil and Infrastructure Engineering, 17(3), 211-220.
• Opricovic, S., & Tzeng, G. H. (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research, 156(2), 445-455.
• Opricovic, S., & Tzeng, G. H. (2007). Extended VIKOR method in comparison with outranking methods. European Journal of Operational Research, 178(2), 514-529.
• Portugal, D. L., Morgado, A. V., & Júnior, O. L. (2011). Location of cargo terminals in metropolitan areas of developing countries: the Brazilian case. Journal of Transport Geography, 19(4), 900-910.
• Rani, P., Jain, D., & Hooda, D. S. (2018). Shapley function based interval-valued intuitionistic fuzzy VIKOR technique for correlative multi-criteria decision making problems. Iranian Journal of Fuzzy Systems, 15(1), 25-54.
• Roso, V., Brnjac, N., & Abramovic, B. (2015). Inland intermodal terminals location criteria evaluation: The case of Croatia. Transportation journal, 54(4), 496-515.
• Shahparvari, S., Nasirian, A., Mohammadi, A., Noori, S., & Chhetri, P. (2020). A GIS-LP integrated approach for the logistics hub location problem. Computers & Industrial Engineering, 146, 106488.
• Sughosh, S. D., Sedhuraman, M. J., & Raj, S. Y. (2017). Prioritizing critical factors for establishing an automotive components manufacturing facility: An AHP-Pareto approach. Journal of Advanced Research in Dynamical & Control Systems, 11-Special Issue, 448-459.
• Tan, C., & Chen, X. (2013). Interval-valued intuitionistic fuzzy multicriteria group decision making based on VIKOR and Choquet integral. Journal of Applied Mathematics, 2013.
• Tzeng, G. H., & Huang, J. J. (2011). Multiple attribute decision making: methods and applications. CRC press.
• Ugboma, C., Ugboma, O., & Ogwude, I. C. (2006). An Analytic Hierarchy Process (AHP) approach to port selection decisions–empirical evidence from Nigerian ports. Maritime Economics & Logistics, 8(3), 251-266.
• Uysal, H., & Yavuz, K. (2014). Selection of logistics centre location via ELECTRE method: A case study in Turkey. International Journal of Business and Social Science, 5(9).
• Wu, L., Gao, H., & Wei, C. (2019). VIKOR method for financing risk assessment of rural tourism projects under interval-valued intuitionistic fuzzy environment. Journal of Intelligent & Fuzzy Systems, 37(2), 2001-2008.
• Yang, Y. C., & Chen, S. L. (2016). Determinants of global logistics hub ports: Comparison of the port development policies of Taiwan, Korea, and Japan. Transport Policy, 45, 179-189.
• Żak, J., & Węgliński, S. (2014). The selection of the logistics center location based on MCDM/A methodology. Transportation Research Procedia, 3, 555-564.
• Zhao, X., Tang, S., Yang, S., & Huang, K. (2013). Extended VIKOR method based on cross-entropy for interval-valued intuitionistic fuzzy multiple criteria group decision making. Journal of Intelligent & Fuzzy Systems, 25(4), 1053-1066.