基于自适应反馈机制的精英教学优化算法

doi:10.16182/j.issn1004731x.joss.201808016

系统仿真学报 ›› 2018, Vol. 30 ›› Issue (8): 2950-2957.doi: 10.16182/j.issn1004731x.joss.201808016

基于自适应反馈机制的精英教学优化算法

李荣雨, 梁栋, 戚桂洪

南京工业大学计算机科学与技术学院,江苏南京 211816

收稿日期:2017-01-06 出版日期:2018-08-10 发布日期:2019-01-08
作者简介:李荣雨(1977-),男,山东,博士,副教授,研究方向为先进控制,机器学习,模拟优化;梁栋(1991-),男,连云港,硕士生,研究方向为机器学习,算法优化。
基金资助:
江苏省高校自然科学基金(12KJB510007)

Adaptive Feedback Elitist Teaching-Learning-Based Optimization Algorithm

Li Rongyu, Liang Dong, Qi Guihong

College of Computer Science and Technology, Nanjing Tech University, Nanjing 211816, China

Received:2017-01-06 Online:2018-08-10 Published:2019-01-08

摘要/Abstract

摘要： 精英教学优化算法(Elitist teaching-learning-based optimization,ETLBO)是一种基于实际班级教学过程的新型优化算法。针对ETLBO算法存在的寻优精度低、稳定性差的问题,提出一种基于自适应反馈机制的精英教学优化算法(Adaptive Feedback ETLBO,AFETLBO)。在学生阶段之后,通过添加自适应反馈机制,将学生分为优等生和差生,且动态调整两者的规模,对差生实行与教师之间的反馈交流,快速向教师靠拢,加强收敛能力;对优等生实行自我学习,进行局部精细搜索。自适应反馈阶段的加入,增加了学习方式,保持了学生的多样性特性,提高全局搜索能力。对6个无约束及5个标准函数的测试结果表明,与其他优化算法相比,AFETLBO算法具有更高的寻优精度和收敛能力。

关键词: 精英教学优化算法, 自适应反馈, 进化算法, 函数优化

Abstract: Elitist teaching-learning-based optimization (ETLBO) is a novel optimization algorithm based on the practical teaching-learning process of the class. An adaptive feedback elitist teaching-learning-based optimization (AFETLBO) algorithm is proposed to solve the problem of low precision and poor stability of the ETLBO. At the end of the learner phase, student can be divided into the top students and the inferior students dynamically by adding the adaptive feedback phase. In this phase, the inferior students should communicate with the teacher and enable themselves to be close to the teacher quickly so as to strengthen the convergence ability. The top students should study by themselves to local search carefully. The adaptive feedback phase can increase the learning style and ensure the diversity of students so as to improve the algorithm’s global search ability. Six unconstrained and five constrained classic tests show that the AFETLBO algorithm has a higher ability of optimization precision and convergence than other algorithms.

Key words: ETLBO, adaptive feedback, evolutionary algorithm, function optimization

中图分类号:

TP301.6

李荣雨, 梁栋, 戚桂洪. 基于自适应反馈机制的精英教学优化算法[J]. 系统仿真学报, 2018, 30(8): 2950-2957.

Li Rongyu, Liang Dong, Qi Guihong. Adaptive Feedback Elitist Teaching-Learning-Based Optimization Algorithm[J]. Journal of System Simulation, 2018, 30(8): 2950-2957.

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基于自适应反馈机制的精英教学优化算法

Adaptive Feedback Elitist Teaching-Learning-Based Optimization Algorithm

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