Study on a Kind of Hybrid Optimization Algorithm for Emergency Materials Scheduling

摘要

Emergency materials scheduling is one of the key links in the process and also is a complicated system engineering that is influenced by multitudinous factors. In order to improve the efficiency of emergency rescue, dynamic change of demand function for emergency materials was analyzed according to the characters of emergency materials scheduling. On this basis, optimization model of emergency materials scheduling have been built to minimize the total casualty losses when the demand doesn't meet and to minimize the total cost which is from distribution center of emergency materials to the rescue point. Considering that the encoder mode of the different evolution and particle swarm optimization algorithm is similarity and the search capability of two types of algorithm is very strong, the Different Evolution (DE) optimization algorithm and Particle Swarm Optimization algorithm (PSO) are combined into an efficient hybrid algorithm (H-PD) to solve this problem. Finally, a case study has been carried out in order to testify validity of this model and its algorithm by using calculating and comparing analysis. The results show that the hybrid optimization algorithm above mentioned can gain smaller loss and larger cost than greedy algorithm, the improved simulated annealing optimization algorithm is reasonable. This model and its algorithm can well reflect the laws of things development and can be of practical and effective value in actual project.