Research On Self-Adaptive Adjustment Of The Fire Disaster Contingency Plan

More and more disasters happen frequently lead to the enormous social losses. In recent years, how to adjust the rescue resources on the basis of control the losses, and how to minimize the total social losses caused by rescue process, has become one of the main direction of disaster research. With the purpose of minimizing the total losses of society, this paper presents a self-adaptive adjustment method for fire disaster contingency plan, which is used in emergency command process.The major research efforts and contributions are as follows:(1) This paper provides a general framework for fire emergency rescue. According to the description about the characteristics of the fire disaster, this paper develops a general model that can be applied in fire emergency rescue. Moreover, this paper overviews the core work to be done, after describing the general model.(2) Based on the idea of heuristic method, this paper classifies the social losses in general framework into two categories, i.e., the social losses already caused and the possible social losses caused by fire continuous burning. And the social losses already caused is further divided into three parts, i.e., the loss because of not meeting the need of resource by rescue forces, the loss on the way of resource transportation and the loss caused by the fire burning and casualties at the disaster scene.(3) Applying the gray prediction method, this paper constructs a set of prediction models on wind, fire, fire burning time and other factors, and gets the predicted values according to these models. Besides, whether resources are adequate and whether it is need to schedule resources in advance is determined by comparing the fire burning time and the time of the existing resources can be used. Considering the factors of predicted firing time, rescue time existing resources can insist on and the transportation time, this paper gives the self-adaptive adjustment rules for rescue resource.(4) Taking bidding protocol as the resource supplier selection protocol, and taking the multi-issue evaluation method as a supplier selection strategy, this paper implements the selection of rescue resources suppliers.(5) To explain the advantage of the adaptive method, this paper designs eight sets of experiments by varying the wind, the burning area and other factors and implements the experiments by evolutionary algorithm and the method given in this paper. According to the experimental results, we can see that the resources needed by evolutionary algorithms is more than the ones needed by the adaptive method in almost all the time. When resources are abundant, the evolutionary algorithm can complete the rescue process within a shorter time. However it shortens the rescue time by wasting of resources, so the total loss of evolutionary algorithms is bigger than that of adaptive method. If the resources are insufficient, the evolutionary algorithm only schedule resources in case of using up all of the resources, while the adaptive method can predict the environmental changes by grey prediction method in previous, and then realize the scheduling process in advance.