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An approach to evaluation of emergency plans for unconventional emergency events based on soft fuzzy rough set

Sun Bingzhen (School of Economics and Management, Xidian University, Xi'an, China)
Ma Weimin (School of Economics and Management, Tongji University, Shanghai China)


ISSN: 0368-492X

Article publication date: 7 March 2016



The purpose of this paper is to present a new method for evaluation of emergency plans for unconventional emergency events by using the soft fuzzy rough set theory and methodology.


In response to the problems of insufficient risk identification, incomplete and inaccurate data and different preference of decision makers, a new model for emergency plan evaluation is established by combining soft set theory with classical fuzzy rough set theory. Moreover, by combining the TOPSIS method with soft fuzzy rough set theory, the score value of the soft fuzzy lower and upper approximation is defined for the optimal object and the worst object. Finally, emergency plans are comprehensively evaluated according to the soft close degree of the soft fuzzy rough set theory.


This paper presents a new perspective on emergency management decision making in unconventional emergency events. Also, the paper provides an effective model for evaluating emergency plans for unconventional events.


The paper contributes to decision making in emergency management of unconventional emergency events. The model is useful for dealing with decision making with uncertain information.



The authors are very grateful to the Editor Dr Magnus Ramage, and the two anonymous referees for their thoughtful comments and valuable suggestions. Some remarks directly benefit from the referees’ comments. This work was partly supported by the National Science Foundation of China (71571090; 71161016), the Fundamental Research Funds for the Central Universities (JB150605) and the Chinese Postdoctoral Science Foundation (XJS15067).


Bingzhen, S. and Weimin, M. (2016), "An approach to evaluation of emergency plans for unconventional emergency events based on soft fuzzy rough set", Kybernetes, Vol. 45 No. 3, pp. 461-473.



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