野草算法及其研究进展  

Invasive Weed Optimization and its Advances

作　　者：韩毅[1] 蔡建湖[1] 李延来[2] 周根贵[1] 

机构地区：[1]浙江工业大学经贸管理学院,杭州310023 [2]东北大学流程工业综合自动化教育部重点实验室,沈阳110004

出　　处：《计算机科学》2011年第3期20-23,共4页Computer Science

基　　金：国家自然科学基金(70971017);浙江省自然科学基金(Y1100854);浙江省社科规划课题成果(10CGGL21YBQ);浙江省科技计划软科学研究项目(2009C35007)资助

摘　　要：野草算法(Invasive Weed Optimization,IWO)是近年来提出的一种简单、有效的基于种群的新颖数值优化算法,自其提出以来正逐渐受到国内外学术界和工程优化领域的关注。IWO算法的提出是受到具有侵略和殖民特性的野草的启发。由于野草在殖民化过程中体现出较强的鲁棒性、自适应性和随机性,因此IWO算法的执行框架尽量模仿野草的殖民化进程。详细阐述了IWO算法的基本原理和流程,总结了其在优化和工程技术领域中的最新研究进展。Invasive Weed Optimization（IWO） is a recently proposed simple and effective population-based novel numerical optimization algorithm.It＇s receiving increasing focuses from academic and engineering optimization fields.IWO is inspired from the invasive and colonizing characteristics of weeds,which tries to imitate the robustness,adaptation and randomness embodied by weeds during the colonizing process.Here,the fundamental principles and framework of IWO were described in detail.Then,the advances of IWO in the current optimization and engineering fields were summed up.

关 键 词：野草算法 工程优化 殖民化 鲁棒性 

分 类 号：TP29[自动化与计算机技术—检测技术与自动化装置]