ELECTRE I-based group decision methodology with risk preferences in an imprecise setting for flexible manufacturing systems

Document Type: Original Manuscript

Authors

1 Department of Industrial Engineering, Faculty of Engineering, Shahed University, Tehran, Iran

2 Young Researchers and Elite Club, South Tehran Branch, Islamic Azad University, Tehran, Iran

3 Department of Industrial Engineering and Mechanical Engineering, Islamic Azad University-Qazvin branch, Qazvin, Iran

10.22094/joie.2019.662.1428

Abstract

A new hesitant fuzzy set (HFS)-ELECTRE for multi-criteria group decision-making (MCGDM) problems is developed in this paper. In real-world applications, the decision makers (DMs)’ opinions are often hesitant for decision problems; thus, considering the exact data is difficult. To address the issue, the DMs’ judgments can be expressed as linguistic variables that are converted into the HFSs, considered as inputs in the ELECTRE method. Meanwhile, an appropriate tool among the fuzzy sets theory and their extensions is the HFSs since the DMs can assign their judgments for an alternative under the evaluation criteria by some membership degrees under a set to decrease the errors. Introduced hesitant fuzzy ELECTRE (HF-ELECTRE) method is elaborated based on the risk preference of each DM with assigning some degrees. Moreover, the weight of each DM is computed and implemented in the proposed procedure to reduce judgments’ errors. Then, a new discordance HF index is provided. Pair-wise comparisons are used for outranking relations regarding HF information. Finally, the validation and verification of the proposed HF-ELECTRE method are demonstrated in a practical example of FMSs.

Graphical Abstract

ELECTRE I-based group decision methodology with risk preferences in an imprecise setting for flexible manufacturing systems

Highlights

  • Proposing hesitant fuzzy version of the ELECTRE method by linguistic terms
  • Computing the weight of each DM by considering the DMs’ risk preferences
  • Introducing a discordance hesitant fuzzy index via hesitant fuzzy distance measure
  • Providing comparative analysis among recent fuzzy decision methods

Keywords

Main Subjects


Atanassov, K. T. (1989). More on intuitionistic fuzzy sets. Fuzzy sets and Systems, 33(1), 37-45.

Atanassov, K. T. (2000). Two theorems for intuitionistic fuzzy sets. Fuzzy sets and Systems, 110(2), 267-269.

Bisdorff, R. (2000). Logical foundation of fuzzy preferential systems with application to the electre decision aid methods. Computers & Operations Research, 27(7), 673-687.

Bojković, N., Anić, I., & Pejčić-Tarle, S. (2010). One solution for cross-country transport-sustainability evaluation using a modified ELECTRE method. Ecological Economics, 69(5), 1176-1186.

Celik, E., Gumus, A. T., & Erdogan, M. (2016). A New Extension of the ELECTRE Method Based Upon Interval Type-2 Fuzzy Sets for Green Logistic Service Providers Evaluation. Evaluation, 44(5), 1-15.

Chen, C.-T., & Hung, W.-Z. (2009). Applying ELECTRE and maximizing deviation method for stock portfolio selection under fuzzy environment Opportunities and Challenges for Next-Generation Applied Intelligence, (pp. 85-91): Springer.

Chen, N., Xu, Z., & Xia, M. (2013). The ELECTRE I multi-criteria decision making method based on hesitant fuzzy sets. International Journal of Information Technology & Decision Making, 14(03), 621-657.

Chen, S.-J. J., Hwang, C.-L., Beckmann, M. J., & Krelle, W. (1992). Fuzzy multiple attribute decision making: methods and applications: Springer-Verlag New York, Inc.

Chen, T.-Y. (2014). An ELECTRE-based outranking method for multiple criteria group decision making using interval type-2 fuzzy sets. Information Sciences, 263, 1-21.

Devi, K., & Yadav, S. P. (2013). A multicriteria intuitionistic fuzzy group decision making for plant location selection with ELECTRE method. The International Journal of Advanced Manufacturing Technology66(9-12), 1219-1229.

Ebrahimnejad, S., Mousavi, S.M., Tavakkoli-Moghaddam, R., Hashemi, H., & Vahdani, B. (2012). A novel two-phase group decision making approach for construction project selection in a fuzzy environment. Applied Mathematical Modelling, 36(9), 4197-4217.

Foroozesh, N., Tavakkoli-Moghaddam, R., Mousavi, S. M., & Vahdani, B., (2017a). Dispatching rule evaluation in flexible manufacturing systems by a new fuzzy decision model with possibilistic-statistical uncertainties, Arabian Journal for Science and Engineering, 42, 2947–2960.

Foroozesh, N., Gitinavard, H., Mousavi, S.M., & Vahdani, B., (2017b). A hesitant fuzzy extension of VIKOR method for evaluation and selection problems under uncertainty, International Journal of Applied Management Science, 9(2), 95-113.

Gitinavard, H., Mousavi, S. M., & Vahdani, B. (2016). A new multi-criteria weighting and ranking model for group decision-making analysis based on interval-valued hesitant fuzzy sets to selection problems. Neural Computing and Applications, 27(6), 1593-1605.

Gitinavard, H., Mousavi, S. M., & Vahdani, B. (2017a). Soft computing-based new interval-valued hesitant fuzzy multi-criteria group assessment method with last aggregation to industrial decision problems. Soft Computing, 21(12), 3247-3265.

Gitinavard, H., Mousavi, S.M., & Vahdani, B., (2017b). Soft computing based on hierarchical evaluation approach and criteria interdependencies for energy decision-making problems: A case study, Energy, 118, 556-577.

Hatami-Marbini, A., & Tavana, M. (2011). An extension of the Electre I method for group decision-making under a fuzzy environment. Omega, 39(4), 373-386.

Hajighasemi, Z., & Mousavi, S.M., (2018). A new approach in failure modes and effects analysis based on compromise solution by considering objective and subjective weights with interval-valued intuitionistic fuzzy sets, Iranian Journal of Fuzzy Systems, 15(1), 139-161.

Jin, B. (2013). ELECTRE method for multiple attributes decision making problem with hesitant fuzzy information. Journal of Intelligent and Fuzzy Systems29(2), 463-468.

Liao, H., & Xu, Z. (2013). A VIKOR-based method for hesitant fuzzy multi-criteria decision making. Fuzzy Optimization and Decision Making, 12(4), 373-392.

Mohagheghi, V., Mousavi, S.M. and Vahdani, B., 2015. A new optimization model for project portfolio selection under interval-valued fuzzy environment. Arabian Journal for Science and Engineering40(11), pp.3351-3361.

Mohagheghi, V.,  Mousavi, S.M., & Vahdani, B., (2017a). Enhancing decision-making flexibility by introducing a new last aggregation evaluating approach based on multi-criteria group decision making and Pythagorean fuzzy sets, Applied Soft Computing, 61, 527-535.

Mohagheghi, V., Mousavi, S.M., Vahdani, B., & Siadat, A., (2017b). A mathematical modeling approach for high and new technology-project portfolio selection under uncertain environments, Journal of Intelligent and Fuzzy Systems, 32, 4069–4079.

Mohagheghi, V., Mousavi, S.M., Aghamohagheghi, M., & Vahdani, B., (2017c). A new approach of multi-criteria analysis for the evaluation and selection of sustainable transport investment projects under uncertainty: A case study, International Journal of Computational Intelligence Systems, 10, 605–626.

Mohagheghi, V., Mousavi, S.M., & Vahdani, B., (2017d). Analyzing project cash flow by a new interval type-2 fuzzy model with an application to construction industry, Neural Computing and Applications, 28, 3393–3411.

Mojtahedi, S. M. H., Mousavi, S. M., & Makui, A. (2010). Project risk identification and assessment simultaneously using multi-attribute group decision making technique. Safety Science, 48(4), 499-507.

Montazer, G. A., Saremi, H. Q., & Ramezani, M. (2009). Design a new mixed expert decision aiding system using fuzzy ELECTRE III method for vendor selection. Expert Systems with Applications, 36(8), 10837-10847.

Moradi, N., Mousavi, S.M., & Vahdani, B., (2018). An interval type-2 fuzzy model for project-earned value analysis under uncertainty, Journal of Multiple-Valued Logic and Soft Computing, 30, 79–103.

Moradi, N., Mousavi, S.M., & Vahdani, B., (2017). An earned value model with risk analysis for project management under uncertain conditions, Journal of Intelligent and Fuzzy Systems, 32, 97–113.

Mousavi, S.M., Vahdani, B., Tavakkoli-Moghaddam, R. and Tajik, N., 2014. Soft computing based on a fuzzy grey group compromise solution approach with an application to the selection problem of material handling equipment. International Journal of Computer Integrated Manufacturing27(6), pp.547-569.

Mousavi, S.M. and Vahdani, B., 2016. Cross-docking location selection in distribution systems: a new intuitionistic fuzzy hierarchical decision model. International Journal of computational intelligence Systems9(1), pp.91-109.

Mousavi, S.M., Vahdani, B. and Behzadi, S.S., 2016. Designing a model of intuitionistic fuzzy VIKOR in multi-attribute group decision-making problems. Iranian Journal of Fuzzy Systems13(1), pp.45-65.

Mousavi, S.M., Foroozesh, N., Gitinavard, H., & Vahdani, B., (2018). Solving group decision-making problems in manufacturing systems by an uncertain compromise ranking method, International Journal of Applied Decision Sciences, 11(1), 55-78.

Mousavi, S.M., Antuchevičienė, J., Zavadskas, E.K., Vahdani, B., & Hashemi, H. , (2019). A new decision model for cross-docking center location in logistics networks under interval-valued intuitionistic fuzzy uncertainty, Transport, 34(1), 30-40.

Qiaoping, S., & Ouyang, J. (2015). Hesitant Fuzzy Multi-Attribute Decision Making Based on TOPSIS With Entropy-Weighted Method. Management Science and Engineering, 9(3), 1-6.

Rao, R. V. (2007). Evaluation of Flexible Manufacturing Systems. Decision Making in the Manufacturing Environment: Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods, 125-137.

Roy, B. (1968). Classement et choix en présence de points de vue multiples. RAIRO-Operations Research-Recherche Opérationnelle, 2(V1), 57-75.

Tavakkoli-Moghaddam, R., Gitinavard, H., Mousavi, S. M., & Siadat, A. (2015). An Interval-Valued Hesitant Fuzzy TOPSIS Method to Determine the Criteria Weights, Outlooks and Insights on Group Decision and Negotiation (pp. 157-169): Springer.

Tavakkoli-Moghaddam, R., Mousavi, S.M. & Heydar, M., (2011). An integrated AHP-VIKOR methodology for plant location selection. International Journal of Engineering-Transactions B: Applications, 24(2), 127.

Torra, V. (2010). Hesitant fuzzy sets. International Journal of Intelligent Systems, 25(6), 529-539.

Torra, V., & Narukawa, Y. (2009). On hesitant fuzzy sets and decision. Paper presented at the Fuzzy Systems, 2009. FUZZ-IEEE 2009. IEEE International Conference on.

Vahdani, B., & Hadipour, H. (2011). Extension of the ELECTRE method based on interval-valued fuzzy sets. Soft Computing, 15(3), 569-579.

Vahdani, B., Mousavi, S. M., Tavakkoli-Moghaddam, R., & Hashemi, H. (2013). A new design of the elimination and choice translating reality method for multi-criteria group decision-making in an intuitionistic fuzzy environment. Applied Mathematical Modelling, 37(4), 1781-1799.

Vahdani, B., Mousavi, S.M. and Ebrahimnejad, S., 2014a. Soft computing-based preference selection index method for human resource management. Journal of Intelligent & Fuzzy Systems26(1), pp.393-403.

Vahdani, B., Mousavi, S.M., Tavakkoli-Moghaddam, R., Ghodratnama, A. and Mohammadi, M., 2014b. Robot selection by a multiple criteria complex proportional assessment method under an interval-valued fuzzy environment. The International Journal of Advanced Manufacturing Technology73(5-8), pp.687-697.

Vahdani, B., Salimi, M., & Mousavi, S.M., (2017). A new compromise solution model based on dantzig-wolf decomposition for solving belief multi-objective nonlinear programming problems with block angular structure, International Journal of Information Technology & Decision Making,  16(2), 333–387.

Wang, J. Q., Wang, D. D., Yu Zhang, H., & Chen, X. H. (2013). Multi-criteria outranking approach with hesitant fuzzy sets. OR Spectrum36(4), 1001-1019.

Wei, G., & Zhang, N. (2014). A multiple criteria hesitant fuzzy decision making with Shapley value-based VIKOR method. Journal of Intelligent & Fuzzy Systems, 26(2), 1065-1075.

Wu, M. C., & Chen, T. Y. (2011). The ELECTRE multicriteria analysis approach based on Atanassov’s intuitionistic fuzzy sets. Expert Systems with Applications38(10), 12318-12327.

Xia, M., & Xu, Z. (2011). Hesitant fuzzy information aggregation in decision making. International Journal of Approximate Reasoning, 52(3), 395-407.

Xu, Z., & Xia, M. (2011). Distance and similarity measures for hesitant fuzzy sets. Information Sciences, 181(11), 2128-2138.

Xu, Z., & Xia, M. (2012). Identifying and eliminating dominated alternatives in multi-attribute decision making with intuitionistic fuzzy information. Applied Soft Computing12(4), 1451-1456.

Xu, Z., & Zhang, X. (2013). Hesitant fuzzy multi-attribute decision making based on TOPSIS with incomplete weight information. Knowledge-Based Systems, 52, 53-64.

Zadeh, L. A. (1965). Fuzzy sets. Information and control, 8(3), 338-353.

Zhang, N., & Wei, G. (2013). Extension of VIKOR method for decision making problem based on hesitant fuzzy set. Applied Mathematical Modelling, 37(7), 4938-4947.

Zhang, Z., Wang, C., Tian, D., & Li, K. (2014). Induced generalized hesitant fuzzy operators and their application to multiple attribute group decision making. Computers & Industrial Engineering, 67, 116-138.