期刊
COMPUTERS & OPERATIONS RESEARCH
卷 31, 期 10, 页码 1703-1725出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/S0305-0548(03)00116-3
关键词
global optimization; direct search method; controlled random search; differential evolution; genetic algorithm; continuous variable
This paper studies the efficiency and robustness of some recent and well known population set-based direct search global optimization methods such as Controlled Random Search, Differential Evolution and the Genetic Algorithm. Some modifications are made to Differential Evolution and to the Genetic Algorithm to improve their efficiency and robustness. All methods are tested on two sets of test problems, one composed of easy but commonly used problems and the other of a number of relatively difficult problems. (C) 2003 Elsevier Ltd. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据