关键词: 演化算法 非静态优化 MEAP 函数优化

Abstract:

Evolutionary algorithms have proved to be powerful in the static optimization field. But how to apply it to the non-static optimization problems that  are more common in the real world is still open. This paper discusses some algorithms that can get acceptable results, and proposes a new algorithm （ME EAP） that is based on classic EA. The new algorithm can learn about environmental changes instantaneously and offer preprocessing that can lead the pop pulation out of swamp and migrate to more hopeful areas if a change occurs, The experimental results show that this algorithm has better performance.

Key words: （evolutionary algorithm non-stationary optimization MEAP function optimization）