Memetic algorithm based on genetic algorithm and improved cuckoo search algorithm for Dynamic Environment

被引：0
|
作者：
Nooraliei, A. [1 ]
Meybodi, M. R. [2 ]
Masoumi, B. [1 ]
机构：
[1] Islamic Azad Univ, Fac Comp & IT Engn, Qazvin Branch, Qazvin, Iran
[2] Amirkabir Univ Technol, Dept Comp Engn, Tehran, Iran
来源：
2016 ARTIFICIAL INTELLIGENCE AND ROBOTICS (IRANOPEN) | 2016年
关键词：
component; Memetic algorithm; dynamic environment; cuckoo search; moving peaks; OPTIMIZATION;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In Many real-world optimization problems, optimization goals, the problem instances or some restrictions may change over time. One of the famous problems in the dynamic environments optimization is moving peaks benchmark function or the moving maximum that behavior is similar to dynamic problems in real-world. In this paper, Memetics algorithm based on genetic algorithm and improved cuckoo search to optimize in dynamic environments is proposed. In the proposed method, we combining genetic algorithm and improved cuckoo search algorithm for dynamic environment has been tested in the moving peaks benchmark as a popular standard dynamic environment with different frequencies and multiple peaks in environment and compared with other algorithms. Experiment results shown that algorithm performance is improved.
引用
收藏
页码：54 / 60
页数：7
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