The purpose of this research is to propose an early restoration for lifeline systems after earthquake disasters. The previous researches show that the optimization of the restoration schedule by using genetic algorith...The purpose of this research is to propose an early restoration for lifeline systems after earthquake disasters. The previous researches show that the optimization of the restoration schedule by using genetic algorithm (GA) is powerful. However, those are not considering the uncertain environment after earthquake disasters. The circumstances of the damage at devastated areas are very changeable due to the aftershock, fire disaster and bad weather. In addition, the restoring works may delay by unexpected accidents. Therefore, it is necessary to obtain the restoration schedule which has robustness, because the actual restoring works could not progress smoothly under the uncertain environment. GA considering uncertainty (GACU) can treat various uncertainties involved, but it is difficult to obtain the robust schedule. In this study, an attempt is made to develop a decision support system of the optimal restoration scheduling by using the improved GACU.展开更多
文摘The purpose of this research is to propose an early restoration for lifeline systems after earthquake disasters. The previous researches show that the optimization of the restoration schedule by using genetic algorithm (GA) is powerful. However, those are not considering the uncertain environment after earthquake disasters. The circumstances of the damage at devastated areas are very changeable due to the aftershock, fire disaster and bad weather. In addition, the restoring works may delay by unexpected accidents. Therefore, it is necessary to obtain the restoration schedule which has robustness, because the actual restoring works could not progress smoothly under the uncertain environment. GA considering uncertainty (GACU) can treat various uncertainties involved, but it is difficult to obtain the robust schedule. In this study, an attempt is made to develop a decision support system of the optimal restoration scheduling by using the improved GACU.
