A new methodology to support group decision-making for IoT-based emergency response systems

Information Systems Frontiers

Volumn 16, Issue 5, 2014, Pages 953-977

  Li, Ni ^a   Sun, Minghui ^a   Bi, Zhuming ^b   Su, Zeya ^a   Wang, Chao ^a  

^a BEIHANG UNIVERSITY   (China)

^b INDIANA UNIVERSITY PURDUE UNIVERSITY FORT WAYNE   (United States)

Author keywords

Consensus modeling; Emergency response system (ERS); Multiple attribute group decision making (MAGDM); Particle swarm optimization (PSO); Partition around medoid (PAM); The Internet of Things (IoT)

Indexed keywords

CLUSTERING ALGORITHMS; DATA ACQUISITION; EMERGENCY SERVICES; INTERNET OF THINGS; PARTICLE SWARM OPTIMIZATION (PSO); SENSOR NETWORKS;

CONSENSUS MODELS; EMERGENCY RESPONSE PLANS; EMERGENCY RESPONSE SYSTEMS; INTERNET OF THING (IOT); INTERNET OF THINGS (IOT); MULTIPLE ATTRIBUTE GROUP DECISION MAKING PROBLEMS (MAGDM); MULTIPLE ATTRIBUTE GROUP DECISION MAKINGS (MAGDM); PARTITIONING AROUND MEDOIDS;

DECISION MAKING;

EID: 84910120247     PISSN: 13873326     EISSN: 15729419     Source Type: Journal    
DOI: 10.1007/s10796-013-9407-z     Document Type: Article

References (118)

1. Akyilidiz, I., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). Wireless sensor network: a survey. Computer Networks, 38(4), 393–422.
2. Anandaligam, G. (1989). A multiagent multiattribute approach for conflict resolution in acid rain impact mitigation. IEEE Transactions on Systems, Man, and Cybernetics, 19(5), 1142–1153.
3. Atzori, L., Iera, A., & Morabito, G. (2010). The Internet of Things: a survey. Computer Networks, 54, 2787–2805.
4. Bai, X., & Yan, H. (2011). Study and design of the safe HIS on the Internet of things. Proceedings of 2011 Fourth International Symposium on Computational Intelligence and Design.
5. Baumgart, L., & Bass, E. (2008). Emergency management decision making during severe weather. Weather and Forecasting, 23, 1268–1279.
6. Belanger, B. (2001). The human side of decision-making. www.au.af.mil/au/awc/awcgate/readings/human.htm.
7. Ben-Arieh, D., & Chen, Z. (2006). Linguistic-labels aggregation and consensus measure for autocratic decision making using group recommendations. IEEE Transactions on Systems, Man, and Cybernetics - Part A, 36, 558–568.
8. Ben-Arieh, D., Easton, T., & Evans, B. (2009). Minimum cost consensus with quadratic cost functions. IEEE Transactions on Systems, Man, and Cybernetics - Part A, 39, 210–217.
9. Bi, Z., & Kang, B. (2010). Enhancement of adaptability of parallel kinematic machines with an adjustable platform. ASME Journal of Manufacturing Science and Engineering, 132(9). doi:10.1115/1.4003120.
10. Bi, Z., & Kang, B. (2011). Sensing and responding to the changes of geometric surfaces in reconfigurable manufacturing and assembly. Enterprise Information Systems. doi:10.1080/17517575.2012.654826.
11. Bi, Z., Lang, S., & Shen, W. (2008). Reconfigurable manufacturing systems: the state of the art. International Journal of Production Research, 46(4), 967–992.
12. Bordogna, G., Fedrizzi, M., & Pasi, G. (1997). A linguistic modeling of consensus in group decision making based on OWA operators. IEEE Transactions on Systems, Man, and Cybernetics - Part A, 27, 126–132.
13. Cabrerizo, F., Moreno, J., Perez, I., & Herrera-Viedma, E. (2010). Analyzing consensus approaches in fuzzy group decision making: advantages and drawbacks. Soft Computing, 14, 451–463.
14. Cabrerizo, F., Perez, I., & Herrera-Viedma, E. (2010). Managing the consensus in group decision making in an unbalanced fuzzy linguistic context with incomplete information. Knowledge-Based Systems, 23, 169–181.
15. Chen, Z. (2011). Quasi real-time evaluation system for seismic disaster based on Internet of things. Proceedings of 2011 IEEE International Conferences on Internet of Things, and Cyber, Physical and Social Computing, pp. 520–524, doi:10.1109/iThings/CPSCom.2011.112.
16. Chen, X., & Fan, Z. (2006). Study on the assessment level of experts based on linguistic assessment matrices. Journal of Systems Engineering, 24(1), 111–115.
17. Chen, X., & Fan, Z. (2007). Study on assessment level of experts based on difference preference information. Systems Engineering - Theory & Practice, 27(2), 27–35.
18. Chen, X., He, Y., & Huang, H. (2011). An approach to automatic development of interlocking logic based on statechart. Enterprise Information Systems, 5(3), 273–286.
19. Chiang, D., Lin, C., & Chen, M. (2011). The adaptive approach for storage assignment by6 mining data of warehouse management system for distribution centres. Enterprise Information Systems, 5(2), 219–234.
20. Chiclana, F., Mata, F., Martinez, L., Herrera-Viedma, E., & Alonso, S. (2008). Integration of a consistency control module with in a consensus decision making model. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 16, 35–53.
21. Dong, Y., Zhang, G., Hong, W., & Xu, Y. (2010). Consensus models for AHP group decision making under row geometric mean prioritization method. Decision Support Systems, 49, 281–289.
22. Duan, L., & Xu, L. (2012). Business intelligence for enterprise systems: a survey. IEEE Transactions on Industrial Informatics, 8(3), 679–687.
23. Duan, L., Xu, L., Guo, F., Lee, J., & Yan, B. (2007). A local-density based spatial clustering algorithm with noise. Information Systems, 32, 978–986.
24. Duan, L., Street, W., & Xu, L. (2011). Healthcare information systems: data mining methods in the creation of a clinical recommender system. Enterprise Information Systems, 5(2), 169–181.
25. Eberhart, R., & Kennedy, J. (1995). A New optimizer using particle swarm theory. Procceedings 6th International Symposium on Micro Machine and Human Science, pp. 39–43, Nagoya, Japan, 1995.
26. Fan, Z., & Liu, Y. (2010). A method for group decision-making based on multi-granularity uncertain linguistic information. Expert Systems with Applications, 37, 4000–4008.
27. Fritzsche, M., Kittel, K., Blankenburg, A., & Vajna, S. (2012). Multidisciplinary design optimisation of a recurve bow based on applications of the autogenetic design theory and distributed computing. Enterprise Information Systems, 6(3), 329–343.
28. Fu, C., & Yang, S. (2010). The group consensus based evidential reasoning approach for multiple attributive group decision analysis. European Journal of Operational Research, 206, 601–608.
29. Fu, C., Zhang, G., Yang, J., & Liu, X. (2011). Study on the contract characteristics of Internet architecture. Enterprise Information Systems, 5(4), 495–513.
30. Gao, H. (2008). Constructing national index system for evaluation of emergency response plans. Business Economy, 009-6043, 11-0039-02.
31. Ghezzi, C., & Pacifici, F. (2008). Evolution of software composition mechanisms: a survey. In D. Lucia, F. Ferrucci, G. Tortora, & M. Tucci (Eds.), Emerging methods, technologies, and process management in software engineering (pp. 3–19). New York: J. Wiley and Sons.
32. Gluhak, A., & van Kranenburg, R. (2012). New instruments of governance for our societies. Proceedings of the 1st International IEEE Workshop on Hot Topics in Pervasive Computing, Lugano.
33. Guo, J., Xu, L., Xiao, G., & Gong, Z. (2012). Improving multilingual semantic interoperation in cross-organizational enterprise systems through concept disambiguation. IEEE Transactions on Industrial Informatics, 8(3), 647–658.
34. Hahn, E. (2010). Judgmental consistency and consensus in stochastic multicriteria decision making. Expert Systems with Applications, 37, 3784–3791.
35. Herrera, F., & Herrera-Viedma, E. (2000). Linguistic decision analysis: steps for solving decision problems under linguistic information. Fuzzy Sets and Systems, 115, 67–82.
36. Herrera, F., Herrera-Viedma, E., & Verdegay, J. (1996). Direct approach processes in group decision making using linguistic OWA operators. Fuzzy Sets and Systems, 79, 175–190.
37. Herrera, F., Herrera-Viedma, E., & Verdegay, J. (1997). A rational consensus model in group decision making using linguistic assessments. Fuzzy Sets and Systems, 88, 31–49.
38. Herrera-Viedma, E., Martinez, L., Mata, F., & Chiclana, F. (2005). A consensus support systems model for group decision making problems with multigranular linguistic preference relations. IEEE Transactions on Fuzzy Systems, 13, 644–658.
39. Herrera-Viedma, E., Alonso, S., Chiclana, F., & Herrera, F. (2007). A consensus model for group decision making with incomplete fuzzy preference elations. IEEE Transactions on Fuzzy Systems, 15, 863–877.
40. Hsu, L., Horng, S., Fan, P., Khan, M., Wang, Y., & Run, R. (2011). MTPSO algorithm for solving planer graph coloring problem. Expert Systems with Applications, 38, 5525–5531.
41. Ingvaldsen, J., & Gulla, J. (2012). Industrial application of semantic process mining. Enterprise Information Systems, 6(2), 139–163.
42. Jiang, Y., Xu, L., Wang, H., & Wang, H. (2009). Influencing factors for predicting financial performance based on genetic algorithms. Systems Research and Behavioral Science, 26(6), 661–673.
43. Kacprzyk, J., Fedrizzi, M., & Nurmi, H. (1992). Group decision making and consensus under fuzzy preferences and fuzzy majority. Fuzzy Sets and Systems, 49, 21–31.
44. Kaufman, L., & Rousseeuw, R. (1987). Clustering by means of medoids. In Y. Dodge (Ed.), Statistical data analysis based on the L, norm (pp. 405–416). North-Holland: Elsevier.
45. Kaufman, L., & Rousseeuw, P. (1990). Finding groups in data: an introduction to cluster analysis. New York: John Wiley & Sons. 0471878766.
46. Kennedy, J., & Eberhart, R. (1995). Particle swarm optimization. Proceedings of IEEE International Conference on Neural Networks, Perth, Australia, vol. IV, pp. 1942–1948.
47. Kennedy, J., Eberhart, R., & Shi, Y. (2001). The particle swarm (pp. 287–325). San Francisco: Swarm Intelligence.
48. Kim, S., & Ahn, B. (1997). Group decision making procedure considering preference strength under incomplete information. Computers and Operations Research, 24, 1101–1112.
49. Kim, S., Choi, S., & Kim, J. (1999). An interactive procedure for multiple attribute group decision making with incomplete information: range-based approach. European Journal of Operational Research, 118, 139–152.
50. Kowalski, K. (1995). A human component to consider in your emergency management plans: the critical incident stress factor. Safety Science, 20, 115–123.
51. Kowalski, K., & Podlesny, A. (2000). The effects of disaster on workers: a study of burnout in investigators of serious accidents and fatalities in the US mining industry. http://stacks.cdc.gov/view/cdc/9430/.
52. Kowalski, K., & Trakofler, C. (2003). Judgment and decision making under stress: an overview for emergency managers. International Journal of Emergency Management, 1(3), 278–289.
53. Kumar, S., Kadow, B., & Lamkin, M. (2011). Challenges with the introduction of radio-frequency identification systems into a manufacturer’s supply chain—a pilot study. Enterprise Information Systems, 5(2), 235–253.
54. Li, L. (2011). Introduction: advanves in e-business engineering. Information Technology and Management, 12(2), 49–50.
55. Li, L., & Liu, J. (2012). An efficient and flexible web services-based multidisciplinary design optimisation framework for complex engineering systems. Enterprise Information Systems, 6(3), 345–371.
56. Li, L., Xu, L., Jeng, H., Naik, D., Allen, T., & Frontini, M. (2008). Creation of environmental health information system for public health service: a pilot study. Information Systems Frontiers, 10(5), 531–543.
57. Li, D., Huang, Z., & Chen, G. (2010). A systematic approach to heterogeneous multiattribute group decision making. Computers and Industrial Engineering, 59, 561–572.
58. Li, F., Xu, L., Jin, C., & Wang, H. (2011a). Intelligent bionic genetic algorithm (IB-GA) and its convergence. Expert Systems with Applications, 38(7), 8804–8811.
59. Li, F., Xu, L., Jin, C., & Wang, H. (2011b). Structure of multi-stage composite genetic algorithm (MSC-GA) and its performance. Expert Systems with Applications, 38(7), 8929–8937.
60. Li, L., Ge, R., Zhou, S., & Valerdi, R. (2012). Guest editorial integrated healthcare information systems. IEEE Transactions on Information Technology in Biomedicine, 16(4), 515–517.
61. Li, N., Yi, W., Bi, Z., Kong, H., & Gong, G. (2012). An optimization method for complex product design. Enterprise Information Systems. doi:10.1080/17517575.2012.743682.
62. Li, S., Xu, L., Wang, X., & Wang, J. (2012). Integration of hrbrid wireless networks in cloud services oriented enterprise information systems. Enterprise Information Systems, 6(2), 165–187.
63. Lin, S., Horng, S., Kao, T., Huang, D., Fahn, C., & Lai, J. (2010). An efficient bi-objective personal assignment based on a hybrid particle swarm optimization model. Expert Systems with Applications, 37, 7825–7830.
64. Liu, Q., & Wang, C. (2012). Multi-terminal pipe routing by Steiner minimal tree and particle swarm optimisation. Enterprise Information Systems, 6(3), 315–327.
65. Liu, B., Cao, S., & He, W. (2011). Distributed data mining for e-business. Information Technology and Management, 12(2), 67–79.
66. Luo, J., Xu, L., Jamont, J., Zeng, L., & Shi, Z. (2007). A flood decision support system on agent grid: method and implementation. Enterprise Information Systems, 1(1), 49–68.
67. Michahelles, F., Thiesse, F., Schmidt, A., & Williams, J. (2007). Pervasive RFID and near field communication technology. IEEE Pervasive Computing, 6(3), 94–96.
68. Park, K., & Kim, S. (1997). Tools for interactive multi-attribute decision making with incompletely identified information. European Journal of Operational Research, 98, 111–123.
69. Parreiras, R., Ekel, P., Martini, S., & Palhares, R. (2010). A flexible consensus scheme for multicriteria group decision making under linguistic assessments. Information Sciences, 180, 1075–1089.
70. Pasley, J. (2005). How BPEL and SOA are changing web services development. IEEE Internet Computing, 9(3), 60–67.
71. Ramanathan, R., & Ganesh, L. (1994). Group preference aggregation methods employed in AHP: an evaluation and an intrinsic process for deriving members’ weightages. European Journal of Operational Research, 79, 249–265.
72. Ren, F., & Quan, C. (2012). Linguistic-based emotion analysis and recognition for measuring consumer satisfaction: an application of affective computing. Information Technology and Management, 13(4), 321–332.
73. Ren, L., Zhang, L., Tao, F., Zhang, X., Luo, Y., & Zhang, Y. (2012). A methodology towards virtualisation-based high performance simulation platform supporting multidisciplinary design of complex products. Enterprise Information Systems, 6(3), 267–290.
74. Robati, A., & Barani, G. (2012). Balanced fuzzy particle swarm optimization. Applied Mathematical Modelling, 36, 2169–2177.
75. Rosello, L., Prats, F., Agell, N., & Sanchez, M. (2010). Measuring consensus in group decisions by means of qualitative reasoning. International Journal of Approximate Reasoning, 51, 441–452.
76. Rousseeuw, P. (1987). Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Computational and Applied Mathematics, 20, 53–65.
77. Saaty, T. (1994). A ratio scale metric and compatibility of ratio scales: the possibility of Arrow’s impossibility theorem. Applied Mathematics Letters, 7, 51–57.
78. Salo, A. (1995). Interactive decision aiding for group decision support. European Journal of Operational Research, 84, 134–149.
79. Shan, S., Wang, L., & Li, L. (2012a). Modeling of emergency response decision-making process using stochastic Petri net: an e-service perspective. Information Technology and Management, 13(4), 363–376.
80. Shan, S., Wang, L., Li, L., & Chen, Y. (2012b). An emergency response decision support system framework for application in e-government. Information Technology and Management, 13(4), 411–427.
81. Sinha, R. (2005). Impact of experience on decision making in emergency situation. Lulea University of Technology, http://epubl.ltu.se/1402-1781/2005/15/LTU-CDUPP-0515-SE.pdf.
82. Streufert, S. (2005). Emergency decision making and metacomplexity. Proceedings of the 2nd International ISCRAM Conference, Brussels, Belgium, 2005.
83. Tang, Z., & Bagchi, K. (2010). Globally convergent particle swarm optimization via ranch-and-bound. Computer and Information Science, 3(4).
84. Theodoridis, S., & Koutroumbas, K. (2006). Pattern recognition. Third Edition, Elsevier.
85. van der Laan, M., Pollardy, K., & Bryan, J. (2002). New Partitioning Around Medoids Algorithm. UC Berkeley Division of Biostatistics Working Paper Series, pp. 105–116.
86. van Sinderen, M., & Almeida, J. (2011). Editorial empowering enterprises through next generation enterprise computing. Enterprise Information Systems, 5(1), 1–8.
87. Vaught, C. (2000). Behavioural and organizational dimensions of underground mine fires. http://stacks.cdc.gov/view/cdc/6398/.
88. Vaught, C., Mallett, L., Kowalski, K., & Brnich, M. (1997). Workers response to realistic evacuation training. http://stacks.cdc.gov/view/cdc/9283/.
89. Wang, C. (2012). Editorial advances in information integration infrastructures supporting multidisciplinery design optimisation. Enterprise Information Systems, 6(3), 265.
90. Wang, C., & Xu, L. (2008). Parameter mapping and data transformation for engineering application integration. Information Systems Frontiers, 10(5), 589–600.
91. Wang, X., & Xu, X. (2012). DIMP:an interoperable solution for software integration and product data exchange. Enterprise Information Systems, 6(3), 291–314.
92. Wang, P., Xu, L., Zhou, S., Fan, Z., Li, Y., & Feng, S. (2010). Novel Bayesian learning method for information aggregation in modular neural networks. Expert Systems with Applications, 37(2), 1071–1074.
93. Wang, L., Wang, J., Hao, L., & Hua, F. (2011). Research on e-government evaluation model based on the principal component analysis. Information Technology and Management, 12(2), 173–185.
94. Wang, L., Zeng, J., & Xu, L. (2011). A decision support system for substage-zoning filling design of rock-fill dams based on particle swarm optimization. Information Technology and Management, 12(2), 111–119.
95. Wetzstein, B., Leitner, P., Rosenberg, F., Dustdar, S., & Leymann, F. (2011). Identifying influential factors of business process performance using dependency analysis. Enterprise Information Systems, 5(1), 79–98.
96. Wickens, C. (1992). Engineering psychology and human performance. 2nd edition, Harper Collins Publication.
97. Wikipedia (2012). “July 2012 Beijing flood,” http://en.wikipedia.org/wiki/July_2012_Beijing_flood, 2012.
98. Xie, K., Chen, G., Wu, Q., Liu, Y., & Wang, P. (2011). Research on the group decision-making about emergency event based on network technology. Information Technology and Management, 12(2), 137–147.
99. Xie, K., Liu, J., Chen, G., Wang, P., & Chaudhry, S. (2012). Group decision-making in an unconventional emergency situation using agile Delphi approach. Information Technology and Management, 13(4), 351–361.
100. Xu, L. (1990). Linguistic approach to the multi-criteria ranking problem. International Journal of Systems Science, 21, 1773–1782.
101. Xu, Z. (2004). Uncertain linguistic aggregation operators based approach to multiple attribute group decision making under uncertain linguistic environment. Information Sciences, 168, 171–184.
102. Xu, Z. (2005). Deviation measures of linguistic preference relations in group decision making. Omega, 33, 249–254.
103. Xu, Z. (2009). An automatic approach to reaching consensus in multiple attribute group decision making. Computers and Industrial Engineering, 56, 1369–1374.
104. Xu, L. (2011a). Enterprise systems: state-of-the-art and future trends. IEEE Transactions on Industrial Informatics, 7(4), 630–640.
105. Xu, L. (2011b). Information architecture for supply chain quality management. International Journal of Production Research, 49(1), 183–198.
106. Xu, Z., & Chen, J. (2007). An interactive method for fuzzy multiple attribute group decision making. Information Sciences, 177, 248–263.
107. Xu, J., & Wu, Z. (2011). A discrete consensus support model for multiple attribute group decision making. Knowledge-Based Systems, 24, 1196–1202.
108. Xu, S., & Xu, L. (2011). Management; a scientific discipline for humanity. Information Technology and Management, 12(2), 51–54.
109. Xu, L., Liang, N., & Gao, Q. (2008). An integrated approach for agricultural ecosystem management. IEEE Transactions on Systems, Man and Cybernetics - Part C, 38(4), 590–599.
110. Xu, L., Tan, W., Zhen, H., & Shen, W. (2008). An approach to enterprise process dynamic modeling supporting enterprise process evolution. Information Systems Frontiers, 10(5), 611–624.
111. Xu, L., Wang, C., Bi, Z., & Yu, J. (2012). AutoAssem: an automated assembly planning system for complex products. IEEE Transactions on Industrial Informatics, 8(3), 669–678.
112. Xu, S., Xu, L., & Basl, J. (2012). Introduction: advances in e-business engineering. Information Technology and Management, 13(4), 201–204.
113. Yin, Y., Fan, Y., & Xu, L. (2012). EMG & EPP-integrated human–machine interface between the paralyzed and rehabilitation exoskeleton. IEEE Transactions on Information Technology in Biomedicine, 16(4), 542–549.
114. Yue, Z. (2011). Developing a straightforward approach for group decision making based on determining weights of decision makers. Applied Mathematical Modelling. doi:10.1016/j.apm.2011.11.041.
115. Zeng, L., Li, L., & Duan, L. (2012a). Business intelligence in enterprise computing environment. Information Technology and Management, 13(4), 297–310.
116. Zeng, L., Li, L., Duan, L., Lu, K., Shi, Z., Wang, M., Wu, W., & Luo, P. (2012b). Distributed data mining: a survey. Information Technology and Management, 13(4), 403–409.
117. Zhou, Z., Valerdi, R., & Zhou, S. (2012). Guest editorial special section on enterprise systems. IEEE Transactions on Industrial Informatics, 8(3), 630.
118. Zhu, X., Wang, H., Xu, L., & Li, H. (2008). Predicting stock index increments by neural networks: the role of trading volume under different horizons. Expert Systems with Applications, 34(4), 3043–3054.