Journal of Frontiers of Computer Science and Technology ›› 2021, Vol. 15 ›› Issue (2): 354-365.DOI: 10.3778/j.issn.1673-9418.2004030

• Theory and Algorithm • Previous Articles     Next Articles

Population Dynamic Optimization Algorithm with Discrete Leslie Age Structure

HUANG Guangqiu, LU Qiuqin   

  1. School of Management, Xi'an University of Architecture and Technology, Xi'an 710055, China
  • Online:2021-02-01 Published:2021-02-01



  1. 西安建筑科技大学 管理学院,西安 710055


To solve some function optimization problems, a new group intelligent optimization algorithm, PDO-DLAS algorithm for short, is proposed by using the dynamic model of population with Leslie age structure. In this algorithm, it is assumed that a population is composed of individuals with different genders and ages. Individuals are automatically divided into several categories according to their gender and age, which greatly increases the diversity of individuals; each operator has a clear function, in which the learning operator can realize the information exchange among individuals of different genders but similar ages; the influence operator can realize the information exchange among individuals of different genders and different ages; the newborn operator can increase the number of strong individuals and the death operator can reduce the number of weak individuals; the evolutionary operator can ensure the global convergence of the algorithm; the Leslie model is used to determine the relevant parameters of the algorithm, enhancing the scientificity of parameter determination; each evolution of the algorithm only deals with the number of individual characteristics 1/250-1/10, which greatly reduces the time complexity. The test results show that the algorithm has superior performance and is suitable for solving optimization problems with high dimension.

Key words: swarm intelligence optimization algorithm, Leslie model, population dynamics, age structure



关键词: 群智能优化算法, Leslie模型, 种群动力学, 年龄结构