首页 | 本学科首页   官方微博 | 高级检索  
     


A Two-Level Function Evaluation Management Model for Multi-Population Methods in Dynamic Environments: Hierarchical Learning Automata Approach
Authors:Javidan Kazemi Kordestani  Amir Masoud Rahmani
Affiliation:Department of Computer Engineering, Science and Research Branch, Islamic Azad University , Tehran, Iran
Abstract:ABSTRACT

The fitness evaluation (FE) management has been successfully applied to improve the performance of multi-population methods for dynamic optimisation problems (DOPs). In this work, we extend one of its variants to address DOPs which was recently proposed by the authors. The aim of our proposal is to increase the efficiency of the FE management. To this end, we propose a technique based on hierarchical learning automata that manages FEs at two level: at first level the algorithm decides which population should be executed, and at the second level it specifies the operation that should be performed by the selected population. A detailed experimental analysis shows the effectiveness of our proposal.
Keywords:Dynamic optimisation problems  differential evolution  moving peaks benchmark  evolutionary computation  hierarchical learning automata  function evaluation management
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号