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Green suppler selection by an integrated method with stochastic acceptability analysis and MULTIMOORA

    Xiaomei Mi   Affiliation
    ; Huchang Liao   Affiliation
    ; Yi Liao Affiliation
    ; Qi Lin Affiliation
    ; Benjamin Lev   Affiliation
    ; AbdullahI Al-Barakati   Affiliation

Abstract

In the process of supplier selection for green supply chain management, uncertain information may appear in alternatives’ performances or experts’ preferences. The stochastic multicriteria acceptability analysis (SMAA) is a beneficial technique to tackling the uncertain information in such a problem and the MULTIMOORA is a robust technique to aggregate alternatives’ utilities. This study dedicates to proposing an SMAA-MULTIMOORA method by considering the advantages of both methods. The integrated method can accept uncertain information as inputs. The steps of the SMAA-MULTIMOORA are illustrated. A case study about the selection of green suppliers is given to show the validity and robustness of the SMAA-MULTIMOORA method.

Keyword : green supplier selection, stochastic information, multi-criteria acceptability analysis, SMAA, MULTIMOORA

How to Cite
Mi, X., Liao, H., Liao, Y., Lin, Q., Lev, B., & Al-Barakati, A. . (2020). Green suppler selection by an integrated method with stochastic acceptability analysis and MULTIMOORA. Technological and Economic Development of Economy, 26(3), 549-572. https://doi.org/10.3846/tede.2020.11964
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Jun 2, 2020
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References

Akman, G. (2015). Evaluating suppliers to include green supplier development programs via fuzzy cmeans and VIKOR methods. Computers & Industrial Engineering, 86, 69–82. https://doi.org/10.1016/j.cie.2014.10.013

Akgül, E., Özemn, M., Aydoğan, E. K., & Türksoy, H. G. (2017). Optimization of the murata vortex spinning machine parameters by the SMAA-MOORA approach. Industria Textila, 68(5), 323–331. https://doi.org/10.35530/IT.068.05.1267

Altuntas, S., Dereli, T., & Yilmaz, M. K. (2015). Evaluation of excavator technologies: Application of data fusion based MULTIMOORA methods. Journal of Civil Engineering and Management, 21(8), 977–997. https://doi.org/10.3846/13923730.2015.1064468

Antucheviciene, J., Kala, Z., Marzouk, M., & Vaidogas, E. R. (2015). Solving civil engineering problems by means of fuzzy and stochastic MCDM methods: Current state and future research. Mathematical Problems in Engineering, 2015, 362579. https://doi.org/10.1155/2015/362579

Awasthi, A., & Kannan, G. (2016). Green supplier development program selection using NGT and VIKOR under fuzzy environment. Computers & Industrial Engineering, 91, 100–108. https://doi.org/10.1016/j.cie.2015.11.011

Bakeshlou, E. A., Khamseh, A. A., Asl, M. A. G., Sadeghi, J., & Abbaszadeh, M. (2017). Evaluating a green supplier selection problem using a hybrid MODM algorithm. Journal of Intelligent Manufacturing, 28(4), 913–927. https://doi.org/10.1007/s10845-014-1028-y

Banaeian, N., Mobli, H., Fahimnia, B., Nielsen, I. E., & Omid, M. (2018). Green supplier selection using fuzzy group decision making methods: A case study from the agri-food industry. Computers & Operations Research, 89, 337–347. https://doi.org/10.1016/j.cor.2016.02.015

Brauers, W. K. M., & Zavadskas, E. K. (2006). The MOORA method and its application to privatization in a transition economy. Control and Cybernetics, 35(2), 445–469.

Brauers, W. K. M., & Zavadskas, E. K. (2010). Project management by multimoora as an instrument for transition economies. Technological and Economic Development of Economy, 16(1), 5–24. https://doi.org/10.3846/tede.2010.01

Brauers, W. K. M., & Zavadskas, E. K. (2012). Robustness of MULTIMOORA: A method for multiobjective optimization. Informatica, 23(1), 1–15.

Büyüközkan, G., & Çifçi, G. (2012). A novel hybrid MCDM approach based on fuzzy DEMATEL, fuzzy ANP and fuzzy TOPSIS to evaluate green suppliers. Experts Systems with Applications, 39(3), 3000–3011. https://doi.org/10.1016/j.eswa.2011.08.162

Chen, X., Zhao, L., & Liang, H. M. (2018). A novel multi-attribute group decision-making method based on the MULTIMOORA with linguistic evaluations. Soft Computing, 22(16), 5347–5361. https://doi.org/10.1007/s00500-018-3030-3

Chithambaranathan, P., Subramanian, N., Gunasekaran, A., & Palaniappan, P. L. K. (2015). Service supply chain environmental performance evaluation using grey based hybrid MCDM approach. International Journal of Production Economics, 166, 163–176. https://doi.org/10.1016/j.ijpe.2015.01.002

Choquet, G. (1953). Theory of capacities. Annales de l’Institut Fourier, 5, 131–295. https://doi.org/10.5802/aif.53

Dorfeshan, Y., Mousavi, S. M., Mohagheghi, V., & Vahdani, B. (2018). Selecting project-critical path by a new interval type-2 fuzzy decision methodology based on MULTIMOORA, MOOSRA and TPOP methods. Computers & Industry Engineering, 120, 160–178. https://doi.org/10.1016/j.cie.2018.04.015

dos Santos, B. M., Godoy, L. P., & Campos, L. M. S. (2019). Performance evaluation of green suppliers using entropy-TOPSIS-F. Journal of Cleaner Production, 207, 498–509. https://doi.org/10.1016/j.jclepro.2018.09.235

Fishman, G. (1996). Monte Carlo: Concepts, algorithms, and applications. Springer. https://doi.org/10.1007/978-1-4757-2553-7

Freeman, J., & Chen, T. (2015). Green supplier selection using an AHP-Entropy-TOPSIS framework. Supply Chain Management, 20(3), 327–340. https://doi.org/10.1108/SCM-04-2014-0142

Gou, X. J., Liao, H. C., Xu, Z. S., & Herrera, F. (2017). Double hierarchy hesitant fuzzy linguistic term set and MULTIMOORA method: A case of study to evaluate the implementation status of haze controlling measures. Information Fusion, 38, 22–34. https://doi.org/10.1016/j.inffus.2017.02.008

Govindan, K., Rajendran, S., Sarkis, J. & Murugesan, P. (2015). Multi criteria decision making approaches for green supplier evaluation and selection: A literature review. Journal of Cleaner Production, 98, 66–83. https://doi.org/10.1016/j.jclepro.2013.06.046

Govindan, K., Kadziński, M., & Sivakumar, R. (2017). Application of a novel PROMETHEE-based method for construction of a group compromise ranking to prioritization of green suppliers in food supply chain. Omega, 71, 129–145. https://doi.org/10.1016/j.omega.2016.10.004

Govindan, K., & Sivakumar, R. (2016). Green supplier selection and order allocation in a low-carbon paper industry: integrated multi-criteria heterogeneous decision-making and multi-objective linear programming approaches. Annals of Operations Research, 238(1–2), 243–276. https://doi.org/10.1007/s10479-015-2004-4

Haeri, S. A. S., & Rezaei, J. (2019). A grey-based green supplier selection model for uncertain environments. Journal of Cleaner Production, 221, 768–784. https://doi.org/10.1016/j.jclepro.2019.02.193

Hafezalkotob, A., Hafezalkotob, A., Liao, H. C., & Herrera, F. (2019). An overview of MULTIMOORA for multi-criteria decision-making: Theory, developments, applications, and challenges. Information Fusion, 51, 145–177. https://doi.org/10.1016/j.inffus.2018.12.002

Hafezalkotob, A., Hafezalkotob, A., Liao, H. C., & Herrera, F. (2020). Interval MULTIMOORA method integrating interval Borda rule and interval best-worst-method-based weighting model: Case study on hybrid vehicle engine selection. IEEE Transactions on Cybernetics, 50(3), 1157–1169. https://doi.org/10.1109/TCYB.2018.2889730

Hafezalkotob, A., Hafezalkotob, A., & Sayadi, M. K. (2016). Extension of MULTIMOORA method with interval numbers: An application in materials selection. Applied Mathematical Modelling, 40(2), 1372–1386. https://doi.org/10.1016/j.apm.2015.07.019

Hamdan, S., & Cheaitou, A. (2017). Supplier selection and order allocation with green criteria: An MCDM and multi-objective optimization approach. Computers & Operations Research, 81, 282–304. https://doi.org/10.1016/j.cor.2016.11.005

Hashemi, S. H., Karimi, A., & Tavana, M. (2015). An integrated green supplier selection approach with analytic network process and improved Grey relational analysis. International Journal of Production Economics, 159, 178–191. https://doi.org/10.1016/j.ijpe.2014.09.027

Hsu, C. W., Kuo, T. C., Chen, S. H., & Hu, A. H. (2013). Using DEMATEL to develop a carbon management model of supplier selection in green supply chain management. Journal of Cleaner Production, 56, 164–172. https://doi.org/10.1016/j.jclepro.2011.09.012

Yazdani, M., Chatterjee, P., Zavadskas, E. K., & Hashemkhani Zolfani, S. (2017). Integrated QFD-MCDM framework for green supplier selection. Journal of Cleaner Production, 142(Part 4), 3728– 3740. https://doi.org/10.1016/j.jclepro.2016.10.095

Kannan, D., Govindan, K., & Rajendran, S. (2015). Fuzzy Axiomatic Design approach based green supplier selection: A case study from Singapore. Journal of Cleaner Production, 96, 194–208. https://doi.org/10.1016/j.jclepro.2013.12.076

Kannan, D., Jabbour, A. B. L. D., & Jabbour, C. J. C. (2014). Selecting green suppliers based on GSCM practices: Using fuzzy TOPSIS applied to a Brazilian electronics company. European Journal of Operational Research, 233(2), 432–477. https://doi.org/10.1016/j.ejor.2013.07.023

Keshavarz Ghorabaee, M., Amiri, M., Zavadskas, E. K., Turskis, Z., & Antucheviciene, J. (2017a). A new hybrid simulation-based assignment approach for evaluating airlines with multiple service quality criteria. Journal of Air Transport Management, 63, 45–60. https://doi.org/10.1016/j.jairtraman.2017.05.008

Keshavarz Ghorabaee, M., Amiri, M., Zavadskas, E. K., Turskis, Z., & Antucheviciene, J. (2017b). Stochastic EDAS method for multi-criteria decision-making with normally distributed data. Journal of Intelligent & Fuzzy Systems, 33(3), 1627–1638. https://doi.org/10.3233/JIFS-17184

Keshavarz Ghorabaee, M., Zavadskas, E. K., Amiri, M., & Esmaeili, A. (2016). Multi-criteria evaluation of green suppliers using an extended WASPAS method with interval type-2 fuzzy sets. Journal of Cleaner Production, 137, 213–229. https://doi.org/10.1016/j.jclepro.2016.07.031

Khaksar, E., Abbasnejad, T., Esmaeili, A., & Tamosaitiene, J. (2016). The effect of green supply chain management practices on environmental performance and competitive advantage: A case study of the cement industry. Technological and Economic Development of Economy, 22(2), 293–308. https://doi.org/10.3846/20294913.2015.1065521

Lahdelma, R., & Salminen, P. (2001). SMAA-2: Stochastic multicriteria acceptability analysis for group decision making. Operations Research, 49(3), 444–454. https://doi.org/10.1287/opre.49.3.444.11220

Lazauskas, M., Kutut, V., & Zavadskas, E. K. (2015). Multicriteria assessment of unfinished construction projects. Gradevinar, 67(4), 319–328.

Liang, X., Jiang, Y. P., & Liu, P. D. (2018). Stochastic multiple-criteria decision making with 2-tuple aspirations: A method based on disappointment stochastic dominance. International Transactions in Operational Research, 25(3), 913–940. https://doi.org/10.1111/itor.12430

Liao, C. N., Fu, Y. K., & Wu, L. C. (2016). Integrated FAHP, ARAS-F and MSGP methods for green supplier evaluation and selection. Technological and Economic Development of Economy, 22(5), 651–669. https://doi.org/10.3846/20294913.2015.1072750

Liao, H. C., Tang, M., Li, Z. M., & Lev, B. (2019a). Bibliometric analysis for highly cited papers in operations research and management science based on Essential Science Indicators. Omega, 88, 223–236. https://doi.org/10.1016/j.omega.2018.11.005

Liao, H. C., Qin, R., Gao, C. Y., Wu, X. L., Hafezalkotob, A., & Herrera, F. (2019b). Score-HeDLiSF: A score function of hesitant fuzzy linguistic term set based on hesitant degrees and linguistic scale functions: An application to unbalanced hesitant fuzzy linguistic MULTIMOORA. Information Fusion, 48, 39–54. https://doi.org/10.1016/j.inffus.2018.08.006

Liao, H. C., Xu, Z. S., Herrera-Viedma, E., & Herrera, F. (2018). Hesitant fuzzy linguistic term set and its application in decision making: A state-of-the art survey. International Journal of Fuzzy System, 20(7), 2084–2110. https://doi.org/10.1007/s40815-017-0432-9

Liou, J. J. H., Tamosaitiene, J., Zavadskas, E. K., & Tzeng, G. H. (2016). New hybrid COPRAS-G MADM Model for improving and selecting suppliers in green supply chain management. International Journal of Production Research, 54(1), 114–134. https://doi.org/10.1080/00207543.2015.1010747

Liu, P. D., Gao, H., & Ma, J. H. (2019). Novel green supplier selection method by combining quality function deployment with partitioned Bonferroni mean operator in interval type-2 fuzzy environment. Information Sciences, 490, 292–316. https://doi.org/10.1016/j.ins.2019.03.079

Lo, H. W., Liou, J. J. H., Wang, H. S., & Tsai, Y. S. (2018). An integrated model for solving problems in green supplier selection and order allocation. Journal of Cleaner Production, 190, 339–352. https://doi.org/10.1016/j.jclepro.2018.04.105

Lu, Z. M., Sun, X. K., Wang, Y. X., & Xu, C. B. (2019). Green supplier selection in straw biomass industry based on cloud model and possibility degree. Journal of Cleaner Production, 209, 995–1005. https://doi.org/10.1016/j.jclepro.2018.10.130

Luo, L., Zhang, C., & Liao, H. C. (2019). Distance-based intuitionistic multiplicative MULTIMOORA method integrating a novel weight-determining method for multiple criteria group decision making, Computers & Industrial Engineering, 131, 82–98. https://doi.org/10.1016/j.cie.2019.03.038

Milton, J. S., & Arnold, J. C. (1995). Introduction to probability and statistics. McGraw-Hill.

Mohammadi, H., Farahani, F. V. Noroozi, M., & Lashgari, A. (2017). Green supplier selection by developing a new group decision-making method under type 2 fuzzy uncertainty. International Journal of Advanced Manufacturing Technology, 93(1–4), 1443–1462. https://doi.org/10.1007/s00170-017-0458-z

Mousakhani, S., Nazari-Shirkouhi, S., & Bozorgi-Amiri, A. (2017). A novel interval type-2 fuzzy evaluation model based group decision analysis for green supplier selection problems: A case study of battery industry. Journal of Cleaner Production, 168, 205–218. https://doi.org/10.1016/j.jclepro.2017.08.154

Pelissari, R., Oliveira, M. C., Amor, S. B., Kandakoglu, A., & Helleno, A. L. (2019). SMAA methods and their applications: A literature review and future research directions. Annals of Operations Research. https://doi.org/10.1007/s10479-019-03151-z

Qin, J. D., Liu, X. W., & Pedrycz, W. (2017). An extended TODIM multi-criteria group decision making method for green supplier selection in interval type-2 fuzzy environment. European Journal of Operational Research, 258(2), 626–638. https://doi.org/10.1016/j.ejor.2016.09.059

Sang, X. Z., & Liu, X. W. (2016). An interval type-2 fuzzy sets-based TODIM method and its application to green supplier selection. Journal of the Operational Research Society, 67(5), 722–734. https://doi.org/10.1057/jors.2015.86

Sen, D. K., Datta, S., Patel, S. K., & Mahapatra, S. S. (2017). Green supplier selection in fuzzy context: A decision-making scenario on application of fuzzy-MULTIMOORA. International Journal of Services and Operations Management, 28(1), 98–140. https://doi.org/10.1504/IJSOM.2017.085907

Shen, L. X., Olfat, L., Govindan, K., Khodaverdi, R., & Diabat, A. (2013). A fuzzy multi criteria approach for evaluating green supplier’s performance in green supply chain with linguistic preferences. Resource Conservation and Recycling, 74, 170–179. https://doi.org/10.1016/j.resconrec.2012.09.006

Tang, X. Y., & Wei, G. W. (2018). Models for green supplier selection in green supply chain management with pythagorean 2-tuple linguistic information. IEEE Access, 6, 18042–18060. https://doi.org/10.1109/ACCESS.2018.2817551

Tervonen, T., & Figueira, J. R. (2008). A survey on stochastic multicriteria acceptability analysis methods. Journal of Multi-Criteria Decision Analysis, 15(1–2), 1–14. https://doi.org/10.1002/mcda.407

Tseng, M. L., Islam, M. S., Karia, N., Fauzi, F. A., & Afrin, S. (2019). A literature review on green supply chain management: Trends and future challenges. Resource Conservation and Recycling, 141, 145–162. https://doi.org/10.1016/j.resconrec.2018.10.009

Ustinovichius, L, & Simanaviciene, R. (2008). The application of stochastic dominance to sensitivity analysis in quantitative multiple criteria decision making. In 5th International Conference on Cooperative Design, Visualization and Engineering (pp. 184–191). Mallorca, Spain. https://doi.org/10.1007/978-3-540-88011-0_25

Wu, X. L., Liao, H. C., Xu, Z. S., Hafezalkotob, A., & Herrera, F. (2018). Probabilistic linguistic MULTIMOORA: A multi-criteria decision making method based on the probabilistic linguistic expectation function and the improved Borda rule. IEEE Transactions on Fuzzy Systems, 26(6), 3688–3702. https://doi.org/10.1109/TFUZZ.2018.2843330

Zaras, K. (2004). Rough approximation of a preference relation by a multi-attribute dominance for deterministic, stochastic and fuzzy decision problems. European Journal of Operational Research, 159(1), 196–206. https://doi.org/10.1016/S0377-2217(03)00391-6

Zou, Q., Zhou, J. Z., Zhou, C., Song, L. X., & Guo, J. (2013). Comprehensive flood risk assessment based on set pair analysis-variable fuzzy sets model and fuzzy AHP. Stochastic Environmental Research and Risk Assessment, 27(2), 525–546. https://doi.org/10.1007/s00477-012-0598-5