Research On Post Disaster Emergency Resource Scheduling Model And Algorithm

In recent years,floods,earthquakes,mudslides and other disasters have occurred frequently,seriously threatening the lives of the general public and causing huge economic losses.After the occurrence of natural disasters,the roads at the affected areas are often damaged,and vehicles are unable to rescue the affected areas.Therefore,a variety of distribution tools need to be used to jointly transport rescue materials.Although China’s perfect transportation network has laid the foundation for joint transportation emergency resources,the climate,road traffic and other influencing factors in the disaster area make it difficult to determine the time and path of joint transportation.Therefore,it is of great significance to study how to reasonably allocate emergency materials and optimize the distribution path under the restriction of road traffic to improve the efficiency of emergency rescue.In this paper,the single cycle and multi cycle joint scheduling problem under road traffic constraints is deeply studied.The main research contents are as follows.On the one hand,for the single-stage emergency material scheduling problem,considering that the road traffic at the disaster site is easily constrained under emergencies,the multi-modal transportation method is used for emergency material scheduling and path planning,and a multi-objective optimization model with the minimization of the average waiting time and rescue cost of the victims as the scheduling objective is constructed;According to the characteristics of the established multi-objective optimization model,the NSGA-II algorithm based on population entropy is designed,and the solution effect of the proposed algorithm is compared with NSGA-II algorithm and the algorithm in the literature.The results show that the proposed algorithm is better than the traditional NSGA-II algorithm and the known literature algorithm,and can obtain better diversity while maintaining better convergence.On the other hand,for the multi-stage and multi cycle emergency material scheduling problem,considering that there are different participants in the emergency rescue decision-making,and there are differences in the needs of the participants,a multi cycle emergency material allocation optimization model is proposed,which takes into account the efficiency and fairness to meet the needs of different participants.In the model,the satisfaction function of disaster victims is constructed with the satisfaction of relief materials and waiting time as parameters,and the government satisfaction function with the highest and lowest scheduling costs acceptable to the government as parameters;According to the characteristics of the model,a shuffled frog leaping Algorithm based on reverse learning mechanism is designed.In this algorithm,not only the position of the worst individual in the population is updated,but also the position of the sub worst individual in the population is updated by using the learning ability of reverse learning mechanism;The rationality of the algorithm is verified by four test functions and numerical examples.Compared with shuffled frog leaping Algorithm and genetic algorithm,the shuffled frog leaping Algorithm based on reverse learning mechanism has higher accuracy and faster convergence speed.