A Mixed Expert Evaluation System and Dynamic Interval-Valued Hesitant Fuzzy Selection Approach
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A Mixed Expert Evaluation System and Dynamic Interval-Valued Hesitant Fuzzy Selection Approach

Authors: Hossein Gitinavard, Mohammad Hossein Fazel Zarandi

Abstract:

In the last decades, concerns about the environmental issues lead to professional and academic efforts on green supplier selection problems. In this sake, one of the main issues in evaluating the green supplier selection problems, which could increase the uncertainty, is the preferences of the experts' judgments about the candidate green suppliers. Therefore, preparing an expert system to evaluate the problem based on the historical data and the experts' knowledge can be sensible. This study provides an expert evaluation system to assess the candidate green suppliers under selected criteria in a multi-period approach. In addition, a ranking approach under interval-valued hesitant fuzzy set (IVHFS) environment is proposed to select the most appropriate green supplier in planning horizon. In the proposed ranking approach, the IVHFS and the last aggregation approach are considered to margin the errors and to prevent data loss, respectively. Hence, a comparative analysis is provided based on an illustrative example to show the feasibility of the proposed approach.

Keywords: Green supplier selection, expert system, ranking approach, interval-valued hesitant fuzzy setting.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1125079

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[1] Handfield, R., et al., Applying environmental criteria to supplier assessment: A study in the application of the Analytical Hierarchy Process. European Journal of Operational Research, 2002. 141(1): p. 70-87.
[2] Yang, Y.-z. and L.-y. Wu. Extension method for green supplier selection. in Wireless Communications, Networking and Mobile Computing, 2008. WiCOM'08. 4th International Conference on. 2008: IEEE.
[3] Hsu, C.-W. and A.H. Hu, Applying hazardous substance management to supplier selection using analytic network process. Journal of Cleaner Production, 2009. 17(2): p. 255-264.
[4] Feyziog̃lu, O. and G. Büyüközkan, Evaluation of green suppliers considering decision criteria dependencies, in Multiple Criteria Decision Making for Sustainable Energy and Transportation Systems. 2010, Springer. p. 145-154.
[5] Tsui, C.-W. and U.-P. Wen, A Hybrid Multiple Criteria Group Decision-Making Approach for Green Supplier Selection in the TFT-LCD Industry. Mathematical Problems in Engineering, 2014. 2014: p. 1-13.
[6] Büyüközkan, G. and G. Çifçi, A novel fuzzy multi-criteria decision framework for sustainable supplier selection with incomplete information. Computers in Industry, 2011. 62(2): p. 164-174.
[7] Datta, S., et al., Green supplier evaluation and selection using VIKOR method embedded in fuzzy expert system with interval–valued fuzzy numbers. International Journal of Procurement Management, 2012. 5(5): p. 647-678.
[8] Kannan, D., et al., Integrated fuzzy multi criteria decision making method and multi-objective programming approach for supplier selection and order allocation in a green supply chain. Journal of Cleaner Production, 2013. 47: p. 355-367.
[9] Sepehriar, A., R. Eslamipoor, and A. Nobari, A new mixed fuzzy-LP method for selecting the best supplier using fuzzy group decision making. Neural Computing and Applications, 2013. 23(1): p. 345-352.
[10] Arshadi Khamseh, A. and M. Mahmoodi, A New Fuzzy TOPSIS-TODIM Hybrid Method for Green Supplier Selection Using Fuzzy Time Function. Advances in Fuzzy Systems, 2014. 2014: p. 11-22.
[11] Chen, T.-Y., An ELECTRE-based outranking method for multiple criteria group decision making using interval type-2 fuzzy sets. Information Sciences, 2014. 263: p. 1-21.
[12] Cao, Q., J. Wu, and C. Liang, An intuitionsitic fuzzy judgement matrix and TOPSIS integrated multi-criteria decision making method for green supplier selection. Journal of Intelligent and Fuzzy Systems, 2014. 28(1): p. 117-126.
[13] Kannan, D., K. Govindan, and S. Rajendran, Fuzzy Axiomatic Design approach based green supplier selection: a case study from Singapore. Journal of Cleaner Production, 2015. 96: p. 194-208.
[14] Celik, E., A.T. Gumus, and M. Erdogan, A New Extension of the ELECTRE Method Based Upon Interval Type-2 Fuzzy Sets for Green Logistic Service Providers Evaluation. Evaluation, 2016. 44(5): p. 1-15.
[15] Govindan, K. and M.B. Jepsen, Supplier risk assessment based on trapezoidal intuitionistic fuzzy numbers and ELECTRE TRI-C: a case illustration involving service suppliers. Journal of the Operational Research Society, 2015. 67(2): p. 339-376.
[16] Zhang, X. and Z. Xu, Hesitant fuzzy QUALIFLEX approach with a signed distance-based comparison method for multiple criteria decision analysis. Expert Systems with Applications, 2015. 42(2): p. 873-884.
[17] Montazer, G.A., H.Q. Saremi, and M. Ramezani, Design a new mixed expert decision aiding system using fuzzy ELECTRE III method for vendor selection. Expert Systems with Applications, 2009. 36(8): p. 10837-10847.
[18] Lin, C.-T. and M.-C. Tsai, Development of an expert selection system to choose ideal cities for medical service ventures. Expert Systems with Applications, 2009. 36(2): p. 2266-2274.
[19] Chai, J., J.N. Liu, and Z. Xu, A new rule-based SIR approach to supplier selection under intuitionistic fuzzy environments. International Journal of Uncertainty, Fuzziness and Knowledge-based Systems, 2012. 20(03): p. 451-471.
[20] Peng, D.-H. and H. Wang, Dynamic hesitant fuzzy aggregation operators in multi-period decision making. Kybernetes, 2014. 43(5): p. 715-736.