关键词: 群智能优化算法, 全局优化, 鼠疫传播动力学模型

Abstract: In order to solve some optimization problems with many local optimal solutions, a new swarm intelligence algorithm, the plague infectious disease optimization (PIDO) algorithm, is proposed by using the dynamic model of plague infectious disease with pulse vaccination and time delay. In the algorithm, it is assumed that there are several villagers living in a village and every villager is characterized by some features. The plague virus is prevalent in the village and the villagers are infected with the disease through effective contact with sick rats. The plague virus attacks a very small part of features of human body. Under the action of the plague virus, the growth state of each villager will be randomly transformed among 4 states of susceptibility, exposure, morbidity and recovery, thus realizing the random search for the global optimal solution. The degree of physical strength of a villager is described by the HHI index. The higher the HHI index of a villager is, the stronger its physical strength will be, also the higher the possibility of its growth will be. The PIDO algorithm has 9 operators such as S_S, S_E, E_E, E_I, E_R, I_I, I_R, R_R, R_S, and each operator only deals with the 1/1000~1/100 of the total number of variables each time. Results of case study show that the PIDO algorithm has the characteristics of fast search speed and global convergence, and is suitable for solving the global optimization problem with higher dimensions.

Key words: swarm intelligence optimization algorithm, global optimization, plague transmission dynamic model