Emergency alternative evaluation under group decision makers: a new method based on entropy weight and DEMATEL

References

• Atanassov, K. T. (1986). Intuitionistic fuzzy-sets. Fuzzy Sets and Systems, 20(1), 87–96. doi: 10.1016/S0165-0114(86)80034-3
   Web of Science ®Google Scholar
• Bian, T., Zheng, H., Yin, L., & Deng, Y. (2018). Failure mode and effects analysis based on D numbers and TOPSIS. Quality and Reliability Engineering International, 34(4), 501–515. doi: 10.1002/qre.2268
   Web of Science ®Google Scholar
• Boran, F. E., & Akay, D. (2014). A biparametric similarity measure on intuitionistic fuzzy sets with applications to pattern recognition. Information Sciences, 255, 45–57. doi: 10.1016/j.ins.2013.08.013
   Web of Science ®Google Scholar
• Cao, X., & Deng, Y. (2019). A new geometric mean FMEA method based on information quality. IEEE Access, 7(1), 95547–95554. doi: 10.1109/ACCESS.2019.2928581
   Google Scholar
• Cao, Z., & Lin, C. T. (2018). Inherent fuzzy entropy for the improvement of EEG complexity evaluation. IEEE Transactions on Fuzzy Systems, 26(2), 1032–1035. doi: 10.1109/TFUZZ.2017.2666789
   Web of Science ®Google Scholar
• Chen, L., & Deng, X. (2018). A modified method for evaluating sustainable transport solutions based on AHP and Dempster–Shafer evidence theory. Applied Sciences, 8(4), 563. doi: 10.3390/app8040563
   Google Scholar
• Chen, S. M., & Tan, J. M. (1994). Handling multicriteria fuzzy decision-making problems based on vague set theory. Fuzzy Sets and Systems, 67, 163–172. doi: 10.1016/0165-0114(94)90084-1
   Web of Science ®Google Scholar
• Chen, L., & Yu, H. (2019). Emergency alternative selection based on an E-IFWA approach. IEEE Access, 7, 44431–44440. doi: 10.1109/ACCESS.2019.2908671
   Web of Science ®Google Scholar
• Dempster, A. P. (1967). Upper and lower probabilities induced by a multivalued mapping. The Annals of Mathematical Statistics, 38325–339. doi: 10.1214/aoms/1177698950
   Google Scholar
• Deng, X. (2018). Analyzing the monotonicity of belief interval based uncertainty measures in belief function theory. International Journal of Intelligent Systems, 33(9), 1869–1879. doi: 10.1002/int.21999
   Web of Science ®Google Scholar
• Deng, Y. (2016). Deng entropy. Chaos, Solitons & Fractals, 91, 549–553. doi: 10.1016/j.chaos.2016.07.014
   Web of Science ®Google Scholar
• Deng, X., & Jiang, W. (2019a). D number theory based game-theoretic framework in adversarial decision making under a fuzzy environment. International Journal of Approximate Reasoning, 106, 194–213. doi: 10.1016/j.ijar.2019.01.007
   Web of Science ®Google Scholar
• Deng, X., & Jiang, W. (2019b). Evaluating green supply chain management practices under fuzzy environment: A novel method based on D number theory. International Journal of Fuzzy Systems, 21(5), 1389–1402. doi: 10.1007/s40815-019-00639-5
   Web of Science ®Google Scholar
• Deng, X., & Jiang, W. (2019c). A total uncertainty measure for D numbers based on belief intervals. International Journal of Intelligent Systems, 34(12), 3302–3316. doi: 10.1002/int.22195
   Web of Science ®Google Scholar
• Deng, X., & Jiang, W. (2020). On the negation of a Dempster-Shafer belief structure based on maximum uncertainty allocation. Information Sciences, 516, 346–352. doi: 10.1016/j.ins.2019.12.080
   Web of Science ®Google Scholar
• Deng, X., Jiang, W., & Wang, Z. (2019). Zero-sum polymatrix games with link uncertainty: A Dempster-Shafer theory solution. Applied Mathematics and Computation, 340, 101–112. doi: 10.1016/j.amc.2018.08.032
   Web of Science ®Google Scholar
• Ding, W., Lin, C. T., & Cao, Z. (2018). Deep neuro-cognitive co-evolution for fuzzy attribute reduction by quantum leaping PSO with nearest-neighbor memeplexes. IEEE Transactions on Cybernetics, 49, 2744–2757. doi: 10.1109/TCYB.2018.2834390
   PubMed Web of Science ®Google Scholar
• Ding, X. F., & Liu, H. C. (2019). A new approach for emergency decision-making based on zero-sum game with Pythagorean fuzzy uncertain linguistic variables. International Journal of Intelligent Systems, 34, 1667–1684. doi: 10.1002/int.22113
   Web of Science ®Google Scholar
• Drabek, T. E., Hoetmer, G. J., & Association, I. C. M. (1991). Emergency management: Principles and practice for local government. Washington DC: Library of Congress: International City Management Association.
   Google Scholar
• Dymova, L., & Sevastjanov, P. (2012). The operations on intuitionistic fuzzy values in the framework of Dempster-Shafer theory. Knowledge-Based Systems, 35, 132–143. doi: 10.1016/j.knosys.2012.04.026
   Web of Science ®Google Scholar
• Esmaelian, M., Tavana, M., Santos Arteaga, F. J., & Mohammadi, S. (2015). A multicriteria spatial decision support system for solving emergency service station location problems. International Journal of Geographical Information Science, 29(7), 1187–1213. doi: 10.1080/13658816.2015.1025790
   Web of Science ®Google Scholar
• Fontela, E., & Gabus, A. (1976). The dematel observer. Geneva: Battelle Geneva Research Center, Dematel.
   Google Scholar
• Gabus, A., & Fontela, E. (1972). World problems, an invitation to further thought within the framework of DEMATEL. Geneva: Battelle Geneva Research Center.
   Google Scholar
• Gao, S., & Deng, Y. (2019). An evidential evaluation of nuclear safeguards. International Journal of Distributed Sensor Networks, 15, 12. doi:10.1177/1550147719894550
   Web of Science ®Google Scholar
• Gao, X., Liu, F., Pan, L., Deng, Y., & Tsai, S. B. (2019). Uncertainty measure based on Tsallis entropy in evidence theory. International Journal of Intelligent Systems, 34(11), 3105–3120. doi: 10.1002/int.22185
   Web of Science ®Google Scholar
• Han, X., & Chen, X. (2014). A d-vikor method for medicine provider selection. In 2014 seventh international joint conference on computational sciences and optimization (pp. 419–423).
   Google Scholar
• Han, Y., & Deng, Y. (2018). A hybrid intelligent model for assessment of critical success factors in high risk emergency system. Journal of Ambient Intelligence and Humanized Computing, 9(6), 1933–1953. doi: 10.1007/s12652-018-0882-4
   Web of Science ®Google Scholar
• Han, Y., Deng, Y., Cao, Z., & Lin, C. T. (2019). An interval-valued Pythagorean prioritized operator-based game theoretical framework with its applications in multicriteria group decision making. Neural Computing and Applications, 10.1007/s00521-019-04014-1, 1–19. doi: 10.1007/s00521-019-04014-1
   Google Scholar
• Han, D., Dezert, J., & Duan, Z. (2016). Evaluation of probability transformations of belief functions for decision making. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 46(1), 93–108. doi: 10.1109/TSMC.2015.2421883
   Web of Science ®Google Scholar
• He, Z., & Jiang, W. (2018). An evidential Markov decision making model. Information Sciences, 467, 357–372. doi: 10.1016/j.ins.2018.08.013
   Web of Science ®Google Scholar
• Hong, D. H., & Choi, C. H. (2000). Multicriteria fuzzy decision-making problems based on vague set theory. Fuzzy Sets and Systems, 114, 103–113. doi: 10.1016/S0165-0114(98)00271-1
   Web of Science ®Google Scholar
• Jiang, W. (2018). A correlation coefficient for belief functions. International Journal of Approximate Reasoning, 103, 94–106. doi: 10.1016/j.ijar.2018.09.001
   Web of Science ®Google Scholar
• Jiang, W., Cao, Y., & Deng, X. (2019). A novel Z-network model based on Bayesian network and Z-number. IEEE Transactions on Fuzzy Systems. doi:10.1109/TFUZZ.2019.2918999
   Google Scholar
• Jiang, W., Huang, C., & Deng, X. (2019). A new probability transformation method based on a correlation coefficient of belief functions. International Journal of Intelligent Systems, 34, 1337–1347. doi: 10.1002/int.22098
   Web of Science ®Google Scholar
• Ju, Y., & Wang, A. (2012). Emergency alternative evaluation under group decision makers: A method of incorporating DS/AHP with extended TOPSIS. Expert Systems with Applications, 39(1), 1315–1323. doi: 10.1016/j.eswa.2011.08.012
   Web of Science ®Google Scholar
• Kang, B., & Deng, Y. (2019). The maximum Deng entropy. IEEE Access, 7(1), 120758–120765.
   Google Scholar
• Li, M., Xu, H., & Deng, Y. (2019). Evidential decision tree based on belief entropy. Entropy, 21(9), 897. doi:10.3390/e21090897
   Web of Science ®Google Scholar
• Mladineo, N., Mladineo, M., & Knezic, S. (2017). Web MCA-based decision support system for incident situations in maritime traffic: Case study of Adriatic Sea. The Journal of Navigation, 70(6), 1312–1334. doi: 10.1017/S0373463317000388
   Web of Science ®Google Scholar
• Nassereddine, M., Azar, A., Rajabzadeh, A., & Afsar, A. (2019). Decision making application in collaborative emergency response: A new PROMETHEE preference function. International Journal of Disaster Risk Reduction, 38, 101–221. doi: 10.1016/j.ijdrr.2019.101221
   Web of Science ®Google Scholar
• Pan, L., & Deng, Y. (2020). An association coefficient of belief function and its application in target recognition system. International Journal of Intelligent Systems, 35, 85–104. doi: 10.1002/int.22200
   Web of Science ®Google Scholar
• Peng, X., Krishankumar, R., & Ravichandran, K. S. (2019). Generalized orthopair fuzzy weighted distance-based approximation (WDBA) algorithm in emergency decision-making. International Journal of Intelligent Systems, 34, 2364–2402. doi: 10.1002/int.22140
   Web of Science ®Google Scholar
• Saaty, T. L. (1980). The analytic hierarchy process: Planning, priority setting, resource allocation (p. 287). New York: MacGraw-Hill International Book Company.
   Google Scholar
• Saksrisathaporn, K., Bouras, A., Reeveerakul, N., & Charles, A. (2016). Application of a decision model by using an integration of AHP and TOPSIS approaches within humanitarian operation life cycle. International Journal of Information Technology & Decision Making, 15(04), 887–918. doi: 10.1142/S0219622015500261
   Google Scholar
• Shafer, G. (1976). A mathematical theory of evidence (Vol. 1). Princeton: Princeton university press.
   Google Scholar
• Shen, F., Ma, X., Li, Z., Xu, Z., & Cai, D. (2018). An extended intuitionistic fuzzy TOPSIS method based on a new distance measure with an application to credit risk evaluation. Information Sciences, 428, 105–119. doi: 10.1016/j.ins.2017.10.045
   Web of Science ®Google Scholar
• Song, Y., Wang, X., Wu, W., Lei, L., & Quan, W. (2017). Uncertainty measure for Atanassovs intuitionistic fuzzy sets. Applied Intelligence, 46(4), 757–774. doi: 10.1007/s10489-016-0863-2
   Web of Science ®Google Scholar
• Wang, L., Wang, Y. M., & Martínez, L. (2017). A group decision method based on prospect theory for emergency situations. Information Sciences, 418-419, 119–135. doi: 10.1016/j.ins.2017.07.037
   Web of Science ®Google Scholar
• Wang, L., Zhang, Z. X., & Wang, Y. M. (2015). A prospect theory-based interval dynamic reference point method for emergency decision making. Expert Systems with Applications, 42(23), 9379–9388. doi: 10.1016/j.eswa.2015.07.056
   Web of Science ®Google Scholar
• Xiao, F. (2017). A novel evidence theory and fuzzy preference approach-based multi-sensor data fusion technique for fault diagnosis. Sensors, 17(11), 2504. doi: 10.3390/s17112504
   PubMed Web of Science ®Google Scholar
• Xiao, F. (2018a). A hybrid fuzzy soft sets decision making method in medical diagnosis. IEEE Access, 6, 25300–25312. doi: 10.1109/ACCESS.2018.2820099
   Web of Science ®Google Scholar
• Xiao, F. (2018b). An improved method for combining conflicting evidences based on the similarity measure and belief function entropy. International Journal of Fuzzy Systems, 20(4), 1256–1266. doi: 10.1007/s40815-017-0436-5
   Web of Science ®Google Scholar
• Xiao, F. (2019). Multi-sensor data fusion based on the belief divergence measure of evidences and the belief entropy. Information Fusion, 46, 23–32. doi: 10.1016/j.inffus.2018.04.003
   Web of Science ®Google Scholar
• Xu, Z. (2008). Intuitionistic fuzzy aggregation operators. IEEE Transactions on Fuzzy Systems, 14(6), 1179–1187.
   Google Scholar
• Xu, Z., & Cai, X. (2008). Dynamic intuitionistic fuzzy multi-attribute decision making. International Journal of Approximate Reasoning, 48(1), 246–262. doi: 10.1016/j.ijar.2007.08.008
   Web of Science ®Google Scholar
• Xu, Z., & Yager, R. R. (2006). Some geometric aggregation operators based on intuitionistic fuzzy sets. International Journal of General Systems, 35(4), 417–433. doi: 10.1080/03081070600574353
   Web of Science ®Google Scholar
• Xu, X., Zheng, J., Yang, J b., Xu, D l., & Chen, Y w. (2017). Data classification using evidence reasoning rule. Knowledge-Based Systems, 116, 144–151. doi: 10.1016/j.knosys.2016.11.001
   Web of Science ®Google Scholar
• Yu, L., & Lai, K. K. (2011). A distance-based group decision-making methodology for multi-person multi-criteria emergency decision support. Decision Support Systems, 51(2), 307–315. doi: 10.1016/j.dss.2010.11.024
   Web of Science ®Google Scholar
• Zadeh, L. A. (1965). Fuzzy sets. Information & Control, 8(3), 338–353. doi: 10.1016/S0019-9958(65)90241-X
   Google Scholar
• Zadeh, L. A. (1986). A simple view of the Dempster-Shafer theory of evidence and its implication for the rule of combination. AI Magazine, 7(2), 85.
   Google Scholar
• Zhang, H., & Deng, Y. (2019). Weighted belief function of sensor data fusion in engine fault diagnosis. Soft Computing. doi:10.1007/s00500-019-04063-7
   Google Scholar
• Zhang, J., Hegde, G. G., Shang, J., & Qi, X. (2016a). Evaluating emergency response solutions for sustainable community development by using fuzzy multi-criteria group decision making approaches: IVDHF-TOPSIS and IVDHF-VIKOR. Sustainability, 8(4), 291. doi: 10.3390/su8040291
   Web of Science ®Google Scholar
• Zhang, J., Hegde, G. G., Shang, J., & Qi, X. (2016b). Evaluating emergency response solutions for sustainable community development by using fuzzy multi-criteria group decision making approaches: IVDHF-TOPSIS and IVDHF-VIKOR. Sustainability, 8(4), 291. doi: 10.3390/su8040291
   Web of Science ®Google Scholar
• Zhao, J., & Deng, Y. (2019). Performer selection in human reliability analysis: D numbers approach. International Journal of Computers Communications & Control, 14(3), 437–452. doi: 10.15837/ijccc.2019.3.3537
   Web of Science ®Google Scholar
• Zhao, B., Tang, T., & Ning, B. (2016). Applying hybrid decision-making method based on fuzzy AHP-WOWA operator for emergency alternative evaluation of unattended train operation metro system. Mathematical Problems in Engineering, 2016. doi: 10.1155/2016/4105079
   Google Scholar
• Zhao, B., Tang, T., Ning, B., & Zheng, W. (2016). Hybrid decision-making method for emergency response system of unattended train operation metro. Promet-Traffic & Transportation, 28(2), 105–115. doi: 10.7307/ptt.v28i2.1760
   Web of Science ®Google Scholar
• Zhou, Q., Mo, H., & Deng, Y. (2020). A new divergence measure of pythagorean fuzzy sets based on belief function and its application in medical diagnosis. Mathematics, 8(1). doi: 10.3390/math8010142
   Google Scholar