Multi-attribute Group Decision-Making for Emergency Evacuation with Storage at Nodes in Fuzzy Environment

Abstract

Emergency evacuation has become of significant importance for emergency management in facing natural and human-made disasters. Decision-making during emergency evacuation is a prominent research area attracting more and more scientists. A crucial issue in emergency decision-making is fuzziness and uncertainty inherent in the process of decisionmaking. In addition, the process of decision-making is becoming more and more complicated because of the variety of aspects to consider. In this regard, this paper proposes an algorithm for emergency evacuation decision-making in fuzzy intuitionistic environment regarding two cases: when attribute weights are known in advance and when they are unknown. To transport the maximum number of aggrieved from the dangerous area to the safe destination, a dynamic flow model with transit arc capacities is constructed. The intermediate nodes in the network have limited capacities and can store the flow in order for the flow to be maximized. Uncertain experts’ evaluations and high level of hesitance are incorporated into the decision-making process in the form of fuzzy intuitionistic numbers. Multi-attribute group decision-making is used to rank the intermediate shelters to evacuate the maximum possible number of aggrieved. In the method, experts have different weights for different attributes, which allows considering the degree of experts’ competence for different attributes. A case study is conducted to illustrate evacuation of the maximum number of aggrieved with intermediate location at nodes with limited capacities in order to transport evacuees to the safe destination based on modified fuzzy intuitionistic TOPSIS.