Memetic algorithm based on genetic algorithm and improved cuckoo search algorithm for dynamic environment

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.