Study of Modeling Earthquake Emergency Rescue Material Scheduling Problems by Multi-objective Optimization Algorithms

To save lives and reduce the property loss, it is important to effectively plan and schedule rescue material distribution after earthquake disaster happening. Due to different constraint factors, such as the time, the number of rescue resource, it is necessary to intelligently analyze and design the distribution solutions based on multi-objective methodologies. Mathematical modeling methods and multi-objective optimization algorithms can be applied to support decision-makers to have an overview on resource distribution with balancing the costs of constrain factors. In this work, a multi-objective model is constructed and analyzed by multi-objective optimization algorithms. Furthermore, an embedded global and local optimization algorithm based on particle swarm optimization and simulated annealing is proposed and applied to the model analysis. Simulation results show that applied and proposed algorithms can effectively analyze the constructed model and adaptively analyze the materials distribution. It can also be a beneficial reference for decision making on relevant disaster rescue scheduling issues.