Development of Evolutionary Design of Experiments to Find Significant Effects for Natural Disaster Prevention

Abstract

For example, in Tsunami evacuation simulation for evaluating the routing factors, the number of simulation trials will increase exponentially, if we will take all possible combination of factors. It is strongly required that reducing the number of simulation run since such simulation based researches will be done in a local community. While it is well known that evolutionary computation will help us in that case if we are able to select a suitable fitness function. Thus, we consider an application of genetic algorithm based search methodology to find significant factors in this paper. The proprieties of tsunami evacuation simulation results are shown and a benchmark problem which has a similar proprieties of the actual simulation results is also introduced. And then, a search algorithm called Evolutionary Design of Experiments is introduced and the effectiveness is evaluated by using the benchmark problems. From the numerical simulation results, the proposed method can find significant factors with the smaller number of simulation executions although the proposed algorithm can not find enough significant factors when it was applied to actual tsunami evacuation simulation results. In the session of discussion, the difference of the properties between actual simulation results and benchmark problem is shown to improve the proposed method.