摘要
多因子优化是一类新的优化问题。多因子进化算法受到多因子遗传模型的启发,利用进化个体的单一种群,能够同时求解跨域的多个优化问题。它属于一种文化基因算法,是智能计算领域新近涌现的研究热点。介绍了多因子进化算法的生物学基础、算法流程,以及文化基因算法的基本概念。然后从工作机理、算法改进、典型应用领域等角度,系统总结了前人的理论和应用成果。最后,指出了将来研究所面临的若干挑战和机遇,以推动学科发展。
Multifactorial optimization is a new category of optimization problems. Inspired by multifactorial inheritance model, multifactorial evolutionary algorithm can solve multiple cross-domain optimization problems simultaneously using a single population of evolving individuals. Regarded as belonging to the realm of memetic algorithm, it has become a hot issue emerging recently in intelligent computation. The biological basis and algorithm procedure of multifactorial evolutionary algorithm and the concept of memetic algorithm are firstly introduced in this paper. Major theoretical and application results are then reviewed critically from the perspective of working mechanism, algorithm improvement and typical application fields. Finally a number of future challenges and opportunities are proposed to help move the field forward.
作者
徐庆征
杨恒
王娜
伍国华
江巧永
XU Qingzheng;YANG Heng;WANG Na;WU Guohua;JIANG Qiaoyong(College of Information and Communication, National University of Defense Technology, Xi＇an 710106, China;College of Systems Engineering, National University of Defense Technology, Changsha 410073, China;School of Computer Science and Engineering, Xi＇an University of Technology, Xi＇an 710048, China)
出处
《计算机工程与应用》
CSCD
北大核心
2018年第11期15-20,40,共7页
Computer Engineering and Applications
基金
国家自然科学基金(No.61305083
No.61603404)
关键词
多因子进化算法
多因子优化
进化算法
选型交配
垂直文化传播
文化基因算法
multifactorial evolutionary algorithm
multifactorial optimization
evolutionary computation
assortativemating
vertical cultural transmission
memetic algorithm
