一类自适应随机搜索算法及DEDS优化

An Adaptive Random Search Algorithm and DEDS Optimization

采用常规的优化方法难以解决一般ＤＥＤＳ的优化问题，本文提出了一种新的基于仿真的自适应随机搜索技术，用于解决这类问题。实践表明，这种方法具有较高的搜索速度及广泛的适用性。

General DEDS optimization problems are intractable via conventional approaches.In this paper,we present a new adaptive random search algorithm based on simulation to solve the problems. Experiments show the algorithm can seek optimal designs effectively and it can also bewidely applied to many other fields.