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doi:10.3808/jei.201700372
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Inexact Fuzzy Stochastic Chance Constraint Programming for Emergency Evacuation in Qinshan Nuclear Power Plant under Uncertainty

C. Z. Huang1,*, S. Nie2, L. Guo3, and Y. R. Fan3,*

  1. Department of Civil Engineering, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
  2. Faculty of Applied Science and Engineering, University of Toronto, Toronto, ON M5S 1A4, Canada
  3. Institute for Energy, Environment and Sustainable Communities, University of Regina, Regina, Saskatchewan S4S 0A2, Canada

*Corresponding author. Tel: +1 306 5854095; fax: +1 306 5854855 E-mail address: charleyhuang33@gmail.com(Z.C.Huang), fan223@uregina.ca (Y.R. Fan).

Abstract


Nuclear power accidents are one of the most dangerous disasters posing a lethal threat to human health and have detrimental effects lasting for decades. Therefore, emergency evacuation is important to minimize injuries and prevent lethal consequences resulting from a nuclear power accident. An inexact fuzzy stochastic chance constrained programming (IFSCCP) method is developed to address various uncertainties in evacuation management problems. It integrates the interval-parameter programming (IPP) and fuzzy stochastic chance constrained programming (FSCCP) methods into a general framework, in which the IPP method addresses the uncertainties presented as intervals defined by crisp lower and upper bounds, and the FCCP treat the dual-uncertainties expressed as fuzzy random variables. The measures of possibility and necessity were employed to convert the fuzzy random variables into crisp values to reflect the decision maker’s pessimistic and optimistic preferences. The IFSCCP model is applied to support nuclear emergency evacuation management in the Qinshan Nuclear Power Site, which is one of the largest nuclear plants in China. The results pro-vide stable intervals for the objective function and decision variables with different fuzzy and probability confidence levels regarding the local residents’ distribution. Nine scenarios are analyzed to reflect the impacts of the imprecision (fuzziness and randomness) associated with the size of the population in a plume emergency planning zone. The results are valuable for supporting local decision makers to generate effective emergency evacuation strategies.

Keywords: decision making, emergency evacuation, nuclear power station, multiple uncertainty, optimization


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