A new SMAA-based methodology for incomplete pairwise comparison matrices: evaluating production errors in the automotive sector

References

• Abastante, F., Corrente, S., Greco, S., Ishizaka, A., & Lami, I. M. (2019). A new parsimonious ahp methodology: Assigning priorities to many objects by comparing pairwise few reference objects. Expert Systems with Applications, 127, 109–120. https://doi.org/10.1016/j.eswa.2019.02.036
   Web of Science ®Google Scholar
• Ammirato, S., Fattoruso, G., & Violi, A. (2022). Parsimonious ahp-dea integrated approach for efficiency evaluation of production processes. Journal of Risk and Financial Management, 15(7), 293. https://doi.org/10.3390/jrfm15070293
   Web of Science ®Google Scholar
• Barzilai, J., Cook, W., & Golany, B. (1987). Consistent weights for judgements matrices of the relative importance of alternatives. Operations Research Letters, 6(3), 131–134. https://doi.org/10.1016/0167-6377(87)90026-5
   Web of Science ®Google Scholar
• Belton, V., & Stewart, T. (2002). Multiple criteria decision analysis: An approach integrated approach. Kluwer Academic.
   Google Scholar
• Benítez, J., Carpitella, S., Certa, A., & Izquierdo, J. (2019). Characterization of the consistent completion of analytic hierarchy process comparison matrices using graph theory. Journal of Multi-Criteria Decision Analysis, 26(1–2), 3–15. https://doi.org/10.1002/mcda.1652
   Web of Science ®Google Scholar
• Bozóki, S., Fülöp, J., & Rónyai, L. (2010). On optimal completion of incomplete pairwise comparison matrices. Mathematical and Computer Modelling, 52(1–2), 318–333. https://doi.org/10.1016/j.mcm.2010.02.047
   Web of Science ®Google Scholar
• Bozóki, S., & Rapcsák, T. (2008). On Saaty’s and Koczkodaj’s inconsistencies of pairwise comparison matrices. Journal of Global Optimization, 42(2), 157–175. https://doi.org/10.1007/s10898-007-9236-z
   Web of Science ®Google Scholar
• Carrizosa, E., & Messine, F. (2007). An exact global optimization method for deriving weights from pairwise comparison matrices. Journal of Global Optimization, 38(2), 237–247. https://doi.org/10.1007/s10898-006-9073-5
   Web of Science ®Google Scholar
• Cavallo, B. (2014). A further discussion of “A Semiring-based study of judgment matrices: Properties and models” [Information Sciences 181 (2011) 2166–2176]. Information Sciences, 287, 61–67. https://doi.org/10.1016/j.ins.2014.07.041
   Web of Science ®Google Scholar
• Cavallo, B. (2017). Computing random consistency indices and assessing priority vectors reliability. Information Sciences, 420, 532–542. https://doi.org/10.1016/j.ins.2017.08.082
   Web of Science ®Google Scholar
• Cavallo, B. (2019). Coherent weights for pairwise comparison matrices and a mixed-integer linear programming problem. Journal of Global Optimization, 75(1), 143–161. https://doi.org/10.1007/s10898-019-00797-8
   Web of Science ®Google Scholar
• Cavallo, B., & Brunelli, M. (2018). A general unified framework for interval pairwise comparison matrices. International Journal of Approximate Reasoning, 93, 178–198. https://doi.org/10.1016/j.ijar.2017.11.002
   Web of Science ®Google Scholar
• Cavallo, B., & D’Apuzzo, L. (2009). A general unified framework for pairwise comparison matrices in multicriterial methods. International Journal of Intelligent Systems, 24(4), 377–398. https://doi.org/10.1002/int.20329
   Web of Science ®Google Scholar
• Cavallo, B., & D’Apuzzo, L. (2012). Deriving weights from a pairwise comparison matrix over an alo-group. Soft Computing, 16(2), 353–366. https://doi.org/10.1007/s00500-011-0746-8
   Web of Science ®Google Scholar
• Cavallo, B., & D’Apuzzo, L. (2020). Preservation of preferences intensity of an inconsistent pairwise comparison matrix. International Journal of Approximate Reasoning, 116, 33–42. https://doi.org/10.1016/j.ijar.2019.10.010
   Web of Science ®Google Scholar
• Chen, K., Kou, G., Tarn, J. M., & Song, Y. (2015). Bridging the gap between missing and inconsistent values in eliciting preference from pairwise comparison matrices. Annals of Operations Research, 235(1), 155–175. https://doi.org/10.1007/s10479-015-1997-z
   Web of Science ®Google Scholar
• D’Orazio, L., Messina, R., & Schiraldi, M. M. (2020). Industry 4.0 and world class manufacturing integration: 100 technologies for a wcm-i4. 0 matrix. Applied Sciences, 10(14), 4942. https://doi.org/10.3390/app10144942
   Google Scholar
• Devaraj, S., Matta, K. F., & Conlon, E. (2009). Product and service quality: The antecedents of customer loyalty in the automotive industry. Production and Operations Management, 10(4), 424–439. https://doi.org/10.1111/j.1937-5956.2001.tb00085.x
   Google Scholar
• Durbach, I., Lahdelma, R., & Salminen, P. (2014). The analytic hierarchy process with stochastic judgements. European Journal of Operational Research, 238(2), 552–559. https://doi.org/10.1016/j.ejor.2014.03.045
   Web of Science ®Google Scholar
• Ergu, D., Kou, G., Peng, Y., & Zhang, M. (2016). Estimating the missing values for the incomplete decision matrix and consistency optimization in emergency management. Applied Mathematical Modelling, 40(1), 254–267. https://doi.org/10.1016/j.apm.2015.04.047
   Web of Science ®Google Scholar
• Escobar, M. T., Aguarón, J., & Moreno-Jiménez, J. M. (2015). Some extensions of the precise consistency consensus matrix. Decision Support Systems, 74, 67–77. https://doi.org/10.1016/j.dss.2015.04.005
   Web of Science ®Google Scholar
• Fattoruso, G. (2022). Multi-criteria decision making in production fields: A structured content analysis and implications for practice. Journal of Risk and Financial Management, 15(10), 431. https://doi.org/10.3390/jrfm15100431
   Web of Science ®Google Scholar
• Fattoruso, G., & Barbati, M. (2021). The usefulness of multi-criteria sorting methods: A case study in the automotive sector. Electronic Journal of Applied Statistical Analysis, 14(2), 277–297.
   Web of Science ®Google Scholar
• Fattoruso, G., Barbati, M., Ishizaka, A., & Squillante, M. (2023). A hybrid ahpsort ii and multi-objective portfolio selection method to support quality control in the automotive industry. Journal of the Operational Research Society, 74(1), 209–224. https://doi.org/10.1080/01605682.2022.2033140
   Web of Science ®Google Scholar
• Gomez-Ruiz, J. A., Karanik, M., & Peláez, J. I. (2010). Estimation of missing judgments in AHP pairwise matrices using a neural network-based model. Applied Mathematics and Computation, 216(10), 2959–2975. https://doi.org/10.1016/j.amc.2010.04.009
   Web of Science ®Google Scholar
• Greco, S., Ehrgott, M., & Figueira, J. (2016). Multiple criteria decision analysis: State of the art surveys. Springer.
   Google Scholar
• Hafizi, M., Jamaludin, S., & Shamil, A. (2019). State of the art review of quality control method in automotive manufacturing industry. IOP Conference Series: Materials Science and Engineering, 530(1), 012034. https://doi.org/10.1088/1757-899X/530/1/012034
   Google Scholar
• Harker, P. (1987a). Alternative modes of questioning in the analytic hierarchy process. Mathematical Modelling, 9(3-5), 353–360. https://doi.org/10.1016/0270-0255(87)90492-1
   Web of Science ®Google Scholar
• Harker, P. (1987b). Incomplete pairwise comparisons in the analytic hierarchy process. Mathematical Modelling, 9(11), 837–848. https://doi.org/10.1016/0270-0255(87)90503-3
   Web of Science ®Google Scholar
• Hu, Y.-C., & Tsai, J.-F. (2006). Backpropagation multi-layer perceptron for incomplete pairwise comparison matrices in analytic hierarchy process. Applied Mathematics and Computation, 180(1), 53–62. https://doi.org/10.1016/j.amc.2005.11.132
   Web of Science ®Google Scholar
• Ishizaka, A., & Nemery, P. (2013). Multi-criteria decision analysis. John Wiley & Sons.
   Google Scholar
• Ishizaka, A., Pearman, C., & Nemery, P. (2012). Ahpsort: An ahp-based method for sorting problems. International Journal of Production Research, 50(17), 4767–4784. https://doi.org/10.1080/00207543.2012.657966
   Web of Science ®Google Scholar
• Kadziński, M., & Michalski, M. (2016). Scoring procedures for multiple criteria decision aiding with robust and stochastic ordinal regression. Computers & Operations Research, 71, 54–70. https://doi.org/10.1016/j.cor.2016.01.007
   Web of Science ®Google Scholar
• Keeney, R. L., & Raiffa, H. (1976). Decisions with multiple objectives: Preferences and value tradeoffs. Wiley.
   Google Scholar
• Kou, G., Ergu, D., Lin, C., & Chen, Y. (2016). Pairwise comparison matrix in multiple criteria decision making. Technological and Economic Development of Economy, 22(5), 738–765. https://doi.org/10.3846/20294913.2016.1210694
   Web of Science ®Google Scholar
• Küçükoğlu, İ., Yagmahan, B., Onayl I, A., Çayhan, E. D., & Ünal, M. (2017). Application of goal programming integrated multi-criteria decision making approaches for the stock area selection problem of an automotive company. International Journal of Supply Chain Management, 6(3), 187–198.
   Google Scholar
• Lahdelma, R., Hokkanen, J., & Salminen, P. (1998). SMAA - stochastic multiobjective acceptability analysis. European Journal of Operational Research, 106(1), 137–143. https://doi.org/10.1016/S0377-2217(97)00163-X
   Web of Science ®Google Scholar
• 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
   Web of Science ®Google Scholar
• Li, K. W., Wang, Z.-J., & Tong, X. (2016). Acceptability analysis and priority weight elicitation for interval multiplicative comparison matrices. European Journal of Operational Research, 250(2), 628–638. https://doi.org/10.1016/j.ejor.2015.09.010
   Web of Science ®Google Scholar
• Liu, F. (2009). Acceptable consistency analysis of interval reciprocal comparison matrices. Fuzzy Sets and Systems, 160(18), 2686–2700. https://doi.org/10.1016/j.fss.2009.01.010
   Web of Science ®Google Scholar
• Lundy, M., Siraj, S., & Greco, S. (2017). The mathematical equivalence of the “spanning tree”and row geometric mean preference vectors and its implications for preference analysis. European Journal of Operational Research, 257(1), 197–208. https://doi.org/10.1016/j.ejor.2016.07.042
   Web of Science ®Google Scholar
• Montmain, J., Labreuche, C., Imoussaten, A., & Trousset, F. (2015). Multi-criteria improvement of complex systems. Information Sciences, 291, 61–84. https://doi.org/10.1016/j.ins.2014.08.027
   Web of Science ®Google Scholar
• Muerza, V., de Arcocha, D., Larrodé, E., & Moreno-Jiménez, J. M. (2014). The multicriteria selection of products in technological diversification strategies: An application to the spanish automotive industry based on ahp. Production Planning & Control, 25(8), 715–728. https://doi.org/10.1080/09537287.2013.798089
   Web of Science ®Google Scholar
• Pelissari, R., Oliveira, M., Amor, S., Kandakoglu, A., & Helleno, A. (2020). Smaa methods and their applications: A literature review and future research directions. Annals of Operations Research, 293(2), 433–493. https://doi.org/10.1007/s10479-019-03151-z
   Web of Science ®Google Scholar
• Petrillo, A., De Felice, F., & Zomparelli, F. (2019). Performance measurement for world-class manufacturing: A model for the italian automotive industry. Total Quality Management & Business Excellence, 30(7-8), 908–935. https://doi.org/10.1080/14783363.2017.1408402
   Web of Science ®Google Scholar
• Ramík, J. (2015). Isomorphisms between fuzzy pairwise comparison matrices. Fuzzy Optimization and Decision Making, 14(2), 199–209. https://doi.org/10.1007/s10700-014-9199-8
   Web of Science ®Google Scholar
• Saaty, T. L. (2013). The modern science of multicriteria decision making and its practical applications: The ahp/anp approach. Operations Research, 61(5), 1101–1118. https://doi.org/10.1287/opre.2013.1197
   Web of Science ®Google Scholar
• Sahu, A. K., Sharma, M., Raut, R. D., Sahu, A. K., Sahu, N. K., Antony, J., & Tortorella, G. L. (2023). Decision-making framework for supplier selection using an integrated mcdm approach in a lean-agile-resilient-green environment: Evidence from indian automotive sector. The TQM Journal, 35(4), 964–1006. (ahead-of-print). https://doi.org/10.1108/TQM-12-2021-0372
   Google Scholar
• Shiraishi, S., & Obata, T. (2002). On a maximization problem arising fromm a positive reciprocal matrix inAHP. Bulletin of Informatics and Cybernetics, 34(2), 91–96. https://doi.org/10.5109/13511
   Google Scholar
• Shiraishi, S., Obata, T., & Daigo, M. (1998). Properties of a positive reciprocal matrix and their application to AHP. Journal of the Operations Research Society of Japan, 41(3), 404–414. https://doi.org/10.15807/jorsj.41.404
   Google Scholar
• Siraj, S., Mikhailov, L., & Keane, J. (2012). Enumerating all spanning trees for pairwise comparisons. Computers & Operations Research, 39(2), 191–199. https://doi.org/10.1016/j.cor.2011.03.010
   Web of Science ®Google Scholar
• Srdjevic, B., Srdjevic, Z., & Blagojevic, B. (2014). First-level transitivity rule method for filling in incomplete pair-wise comparison matrices in the analytic hierarchy process. Applied Mathematics & Information Sciences, 8(2), 459–467. https://doi.org/10.12785/amis/080202
   Google Scholar
• Tekile, H. A., Brunelli, M., & Fedrizzi, M. (2023). A numerical comparative study of completion methods for pairwise comparison matrices. Operations Research Perspectives, 10, 100272. https://doi.org/10.1016/j.orp.2023.100272
   Web of Science ®Google Scholar
• Ülengin, F., Önsel, Ş., Aktas, E., Kabak, Ö., & Özayd In, Ö. (2014). A decision support methodology to enhance the competitiveness of the turkish automotive industry. European Journal of Operational Research, 234(3), 789–801. https://doi.org/10.1016/j.ejor.2013.09.044
   Web of Science ®Google Scholar
• Ulewicz, R. (2018). Outsorcing quality control in the automotive industry. MATEC Web of Conferences, 183, 03001. (https://doi.org/10.1051/matecconf/201818303001
   Google Scholar
• Wu, Z., & Xu, J. (2012). A consistency and consensus based decision support model for group decision making with multiplicative preference relations. Decision Support Systems, 52(3), 757–767. https://doi.org/10.1016/j.dss.2011.11.022
   Web of Science ®Google Scholar
• Xu, T., Moon, D. H., & Baek, S. G. (2012). A simulation study integrated with analytic hierarchy process (ahp) in an automotive manufacturing system. SIMULATION, 88(4), 450–463. https://doi.org/10.1177/0037549711407781
   Google Scholar
• Zhou, X., Hu, Y., Deng, Y., Chan, F., & Ishizaka, A. (2018). A DEMATEL-based completion method for incomplete pairwise comparison matrix in AHP. Annals of Operations Research, 271(2), 1045–1066. https://doi.org/10.1007/s10479-018-2769-3
   Web of Science ®Google Scholar