A rough multicriteria approach for evaluation of the supplier criteria in automotive industry
DOI:
https://doi.org/10.31181/dmame180182vKeywords:
Rough AHP, Supplier Criteria, Fuzzy AHP, Logistics, QualityAbstract
Ensuring costs reduction and increasing competitiveness and satisfaction of end users are the goals of each participant in the supply chain. Taking into account these goals, the paper proposes methodology for defining the most important criteria for suppliers’ evaluation. From a set of twenty established criteria, i.e. four sets of criteria: finances, logistics, quality and communication and business including its sub-criteria, we have allocated the most important ones for supplier selection. Analytic Hierarchy Process (AHP) based on rough numbers is presented to determine the weight of each evaluation criterion. For the criteria evaluation we have used knowledge from the expert in this field. The efficacy of the proposed evaluation methodology is demonstrated through its application to the company producing metal washers for the automotive industry. Next a sensitivity analysis is carried out in order to show the stability of the model. For checking stability the AHP method in conventional form is used in combination with fuzzy logic.
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References
Birgün Barla, S. (2003). A case study of supplier selection for lean supply by using a mathematical model. Logistics Information Management, 16(6), 451-459.
Büyüközkan, G., & Göçer, F. (2017). Application of a new combined intuitionistic fuzzy MCDM approach based on axiomatic design methodology for the supplier selection problem. Applied Soft Computing, 52, 1222-1238.
Chai, J., & Liu, J. N. (2014). A novel believable rough set approach for supplier selection. Expert Systems with Applications, 41 (1), 92-104
Chan, F. T., & Kumar, N. (2007). Global supplier development considering risk factors using fuzzy extended AHP-based approach. Omega, 35 (4), 417-431.
Davis, T. (1993). Effective supply chain management. Sloan management review, 34 (4), 35.
Düntsch, I., & Gediga, G. (1997). The rough set engine GROBIAN. In: A. Sydow (ed.), Proceedings 15th IMACS World Congress, Berlin, Wissenschaft und Technik Verlag, Berlin 4, 613-618.
Fallahpour, A., Olugu, E. U., & Musa, S. N. (2017). A hybrid model for supplier selection: integration of AHP and multi expression programming (MEP). Neural Computing and Applications, 28(3), 499-504.
Fazlollahtabar, H., Vasiljević, M., Stević, Ž., & Vesković, S. (2017). Evaluation of supplier criteria in automotive industry using rough AHP. The 1st International Conference on Management, Engineering and Environment ICMNEE, 186-197.
Gencer, C., & Gürpinar, D. (2007). Analytic network process in supplier selection: A case study in an electronic firm. Applied mathematical modelling, 31 (11), 2475-2486.
Jamil, N., Besar, R., & Sim, H. K. (2013). A study of multicriteria decision making for supplier selection in automotive industry. Journal of Industrial Engineering, 2013, Article ID 841584, 1-22.
Kagnicioglu, C. H. (2006). A fuzzy multiobjective programming approach for supplier selection in a supply chain. The Business Review, 6(1), 107-115.
Khoo, L. P., & Zhai, L. Y. (2001). A prototype genetic algorithm-enhanced rough set-based rule induction system. Computers in industry, 46(1), 95-106.
Kilic, H. S. (2013). An integrated approach for supplier selection in multi-item/multi-supplier environment. Applied Mathematical Modelling, 37 (14), 7752-7763.
Liang, D., Xu, Y., Liu, D. (2017). Three-way decisions with intuitionistic fuzzy decision-theoretic rough sets based on point operators. Information Sciences 375, 183–201.
Mukhametzyanov, I., & Pamučar, D. (2017). Multi-criteria decision making methods: Sensivity of results in variation of estimaons of alternatives by criteria. The 1st International Conference on Management, Engineering and Environment ICMNEE, 2-24
Muralidharan, C., Anantharaman, N., & Deshmukh, S. G. (2002). A multi‐criteria group decision making model for supplier rating. Journal of supply chain management, 38 (3), 22-33.
Nauman, M., Nouman, A., & Yao, J. T. (2016). A three-way decision making approach to malware analysis using probabilistic rough sets. Information Sciences, 374, 193–209.
Özbek, A. (2015). Supplier Selection with Fuzzy TOPSIS. Journal of Economics and Sustainable Development, 6 (18), 114-125.
Pamučar, D., Mihajlović, M., Obradović, R., & Atanasković, P. (2017a). Novel approach to group multi-criteria decision making based on interval rough numbers: Hybrid DEMATEL-ANP-MAIRCA model. Expert Systems with Applications, 88, 58-80
Pamučar, D., Božanić, D., & Ranđelović, A. (2017b). Multi-criteria decision making: An example of sensitivity analysis. Serbian Journal of Management, 12 (1), 1-27.
Pawlak, Z. (1991). Rough sets: Theoretical aspects of reasoning about data. Kluwer Academic Publishing: Dordrecht.
Pawlak, Z. (1982). Rough sets. International Journal of Computer & Information Sciences, 11(5), 341–356
Rezaei, J., Fahim, P. B., & Tavasszy, L. (2014). Supplier selection in the airline retail industry using a funnel methodology: Conjunctive screening method and fuzzy AHP. Expert Systems with Applications, 41(18), 8165-8179.
Roy, J., Chatterjee, K., Bandhopadhyay, A., & Kar, S. (2016). Evaluation and selection of Medical Tourism sites: A rough AHP based MABAC approach. arXiv:1606.08962.
Saaty, T. L., & Vargas, L. G. (2012). Models, methods, concepts & applications of the analytic hierarchy process. Springer Science & Business Media, 175 (2), 1-346.
Sawik, T. (2010). Single vs. multiple objective supplier selection in a make to order environment. Omega, 38 (3), 203-212.
Shidpour, H., Da Cunha, C., & Bernard, A. (2016). Group multi-criteria design concept evaluation using combined rough set theory and fuzzy set theory. Expert Systems with Applications, 64, 633-644.
Song, W., Ming, X., Wu, Z., & Zhu, B. A. (2014). Rough TOPSIS approach for failure mode and effects analysis in uncertain environments. Quality and Reliability Engineering International, 30(4), 473-486.
Song, W., Ming, X., & Wu, Z. (2013). An integrated rough number-based approach to design concept evaluation under subjective environments. Journal of Engineering Design, 24 (5), 320-341.
Stević, Ž. (2017a). Criteria for supplier selection: A literature review. International Journal of Engineering, Business and Enterprise Applications, 19(1), 23-27.
Stević, Ž. (2017b). Evaluation of supplier selection criteria in agricultural company using fuzzy AHP method, 22th International Scientific Conference Strategic Management and Decision Support Systems in Strategic Management, 607-612.
Stević, Ž. (2017c). Modeling performance of logistics subsystems using fuzzy approach. Transport & Logistics: The International Journal, 17 (42), 30-39.
Stević, Ž., Pamučar, D., Zavadskas, K.E., Ćirović, G., & Prentkovskis, O. (2017a). The Selection of Wagons for the Internal Transport of a Logistics Company: A Novel Approach Based on Rough BWM and Rough SAW Methods. Symmetry, 9 (11), 1-25.
Stević, Ž., Pamučar, D., Vasiljević, M., Stojić, G., & Korica, S. (2017b). Novel Integrated Multi-Criteria Model for Supplier Selection: Case Study Construction Company. Symmetry, 9(11), 1-25.
Stević, Ž., Tanackov, I., Vasiljević, M., Novarlić, B., & Stojić, G. (2016). An integrated fuzzy AHP and TOPSIS model for supplier evaluation. Serbian Journal of Management, 11(1), 15-27.
Ting, S. C., & Cho, D .I. (2008). An integrated approach for supplier selection and purchasing decisions. Supply Chain Management: An International Journal, 13(2), 116-127.
Tiwari, V., Jain, P. K., & Tandon, P. (2016). Product design concept evaluation using rough sets and VIKOR method. Advanced Engineering Informatics, 30(1), 16-25.
Uygun, Ö., Kaçamak, H., Ayşim, G., & Şimşir, F. (2013). Supplier Selection for Automotive Industry Using Multi-Criteria Decision Making Techniques. Turkish Online Journal of Science & Technology, 3(4), 25-38.
Van Weele, A. J. (2009). Purchasing and supply chain management: Analysis, strategy, planning and practice. Cengage Learning EMEA.
Wang, T. K., Zhang, Q., Chong, H. Y., & Wang, X. (2017). Integrated supplier selection framework in a resilient construction supply chain: An approach via analytic hierarchy process (AHP) and grey relational analysis (GRA). Sustainability, 9(2), 28-39.
Wang, W. P. (2010). A fuzzy linguistic computing approach to supplier evaluation. Applied Mathematical Modelling, 34 (10), 3130-3141.
Yücenur, G. N., Vayvay, Ö., & Demirel, N. Ç. (2011). Supplier selection problem in global supply chains by AHP and ANP approaches under fuzzy environment. The International Journal of Advanced Manufacturing Technology, 56(5), 823-833.
Zhai, L. Y., Khoo, L. P., & Zhong, Z. W. (2008). A rough set enhanced fuzzy approach to quality function deployment. The International Journal of Advanced Manufacturing Technology, 37 (5), 613-624.
Zhai, L. Y., Khoo, L. P., & Zhong, Z. W. (2009). A rough set based QFD approach to the management of imprecise design information in product development. Advanced Engineering Informatics, 23(2), 222-228.
Zhu, G. N., Hu, J., Qi, J., Gu, C. C., & Peng, Y. H. (2015). An integrated AHP and VIKOR for design concept evaluation based on rough number. Advanced Engineering Informatics, 29(3), 408-418.
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