## Materials and Methods
### Problem Formulation and Matrix Construction  
The principal issue in emergency response are the identification of the optimal path(s) (or route(s) to the location of the emergency; in extreme emergencies the issue may extend to identifying available paths. Emergency response management centres must be aware of the DOE and the current situation relating to emergency service resources. Additionally, emergency management centres must apply strategic management to manage dynamic'real-time' emergency situations; such strategies will involve the deployment of resources and the optimal routing of the resources matching the resources to the prevailing emergency as it develops 'on-the-ground'.  
We may formulate a conceptual emergency domain as follows:  
1. The _Hedge-Emergency-DSS_: the objective function is designed to maximise the operational efficiency of the emergency management decision making when dealing with multiple emergencies;
2. Let \(X^{S}=\{X_{1}^{S},X_{2}^{S},\ldots,X_{m}^{S}\}\) be a set of adjectives called _Kansei_ words to consider available alternatives in evaluating an emergency situation where \(m\) is the number of _Kansei_ words;
3. Assume that quantification of human sensibilities using in decision making can be presented in an emergency situation domain \(S\); Optimized _Kansei_ words in \(X^{S}\) are used to evaluate alternatives which belong to the criteria and factors \(S\);
4. Let \(W_{m}^{S}=\{W_{m}^{-},W_{m}^{+}\}\) be adjective pairs of _Kansei_ words belonging to \(X_{m}^{S}\);
5. Let \(P\) be decision makers' input the proposed system in \(S\);
6. In evaluation of alternative \(X_{j}^{S}\), its _Kansei_ weight \(w_{ij}^{t}\) can be represented by the _i-th Kansei_ word of the _j-th_ alternative considered by the _t-th_ decision maker.
7. Let \(V^{S}=\{V_{1}^{S},V_{2}^{S},\ldots,V_{h}^{S}\}\) be a set of transportation vehicles \(S\), where \(h\) is the number of emergency vehicles.
8. Let quantitative semantics work in the mapping of \((HA)\), presented in linguistic values for \(\left(w_{j}\right)\) fall in the range [0,1].
9. Let a decision maker calculate an objective function value for \(\left(Q_{j}\left(X\right)\right)\) in the emergency domain
10. Group Decision Making (GDM) is a solution for two or more decision makers to aggregate their preferences. Let \(E^{S}=\{e_{1}^{S},e_{2}^{S},\ldots,e_{q}^{S}\}\) be a set of experts for a selection of disaster strategies, where \(q\) is the number of experts. Let \(G^{S}=\{S_{1}^{S},S_{2}^{S},\ldots,S_{c}^{S}\}\) be a set of expert groups, where \(c\) is the number of expert groups. Let \(p_{l}^{S}|(t=1,\ldots,c)\) represent disaster strategies determined by an expert \(e_{l}^{S}\).
11. In an emergency domain \(S\), each expert may determine an approach that matches the appropriate emergency management strategies based on the results of _Kansei_ evaluation.  
Tor identify disaster strategies \(p_{t}^{S}\), an expert \(e_{t}^{S}\) provides his/her preference in a five-point scale definition (0: _oppose_, 0.25: _almost oppose_, 0.5: _have no preference_, 0.75: _almost agree_, 1: _agree_) to evaluate companies. We construct a Decision matrix \(A_{q\times k}^{S}=(a_{ij}^{S})_{(q\times k)}\), where \(k=l+m+g\) is the total number of _Kansei_ words, disaster quantitative and qualitative factors, and \(q\) is the number of experts.