种群具有离散Leslie年龄结构的动力学优化算法

doi:10.3778/j.issn.1673-9418.2004030

摘要/Abstract

摘要：

为了解决一些函数优化问题，采用种群具有Leslie年龄结构的动力学模型提出了一种新型群智能优化算法，简称PDO-DLAS算法。在该算法中，假设某种群由具有不同性别、不同年龄的生物个体组成，个体依据其性别和年龄被自动划分成若干类，增加了个体的多样性；每个算子具有明确功能，其中学习算子可实现性别不同但年龄相近个体之间的信息交换；影响算子可实现不同性别、不同年龄个体之间的信息交换；新生算子可增加强壮个体数，死亡算子可以减少虚弱个体数；进化算子可确保算法具有全局收敛性；依据Leslie模型确定该算法中的相关参数，提升了参数确定的科学性；该算法每次进化只处理个体特征数的1/250~1/10，从而使时间复杂度大幅降低。测试结果表明，该算法具有较优越的性能，适于求解维数较高的优化问题。

关键词: 群智能优化算法, Leslie模型, 种群动力学, 年龄结构

Abstract:

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

黄光球, 陆秋琴. 种群具有离散Leslie年龄结构的动力学优化算法[J]. 计算机科学与探索, 2021, 15(2): 354-365.

HUANG Guangqiu, LU Qiuqin. Population Dynamic Optimization Algorithm with Discrete Leslie Age Structure[J]. Journal of Frontiers of Computer Science and Technology, 2021, 15(2): 354-365.

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