基于离散混合蛙跳算法的地震应急物资调度

A mathematical model of emergency material scheduling after earthquakes is built. The model evaluates the emergency degree of each disaster area based on the disaster situation and designs a method to split the demand of the disaster area, improving the efficiency of vehicle utilization. To solve the model, this paper proposes a discrete shuffled frog leaping algorithm with multi-resource learning. The multiple information sources introduced by the proposed algorithm can expand the search direction and reduce the assimilation speed of the population in the algorithm. Second, the worst individual in each subgroup can learn the effective information in the population to improve the convergence accuracy of the algorithm. Experimental results show that the proposed algorithm can obtain a higher-quality scheduling scheme and has good scalability for the scale of emergency material scheduling.