Casualty rescue path optimization in cities in early post-earthquake period

Abstract

After an earthquake, decision makers are required to make a rapid response. In order to minimize the damage caused after an earthquake disaster and improve the efficiency of casualty rescue, scientific and effective casualty transportation dispatching is required. Especially for small and medium-sized cities where materials are scarce and transportation is inconvenient, effective optimization of casualty dispatching can minimize the amount of casualties and improve rescue efficiency. Therefore, this paper analyzes and researches the post-earthquake casualty rescue problem against the background of the initial rescue stage after the earthquake disaster in small and medium-sized cities, so as to provide the government and other relevant post-earthquake emergency logistics management departments with decision-making references. By establishing a casualty rescue planning model for small and medium-sized cities pursuing the minimization of total rescue time, and applying genetic algorithm to solve the path optimization model with soft time window constraints. The empirical analysis substitutes the street city simulation data of Wuxi County, Chongqing, and generates the stochastic solution and the optimal solution by MATLAB software, and the study finds that the optimal solution has significantly better travel time than the stochastic solution.