Recent advances in multifactorial evolutionary algorithm

doi:10.3778/j.issn.1002-8331.1803-0014

Computer Engineering and Applications ›› 2018, Vol. 54 ›› Issue (11): 15-20.DOI: 10.3778/j.issn.1002-8331.1803-0014

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Recent advances in multifactorial evolutionary algorithm

XU Qingzheng1, YANG Heng1, WANG Na1, WU Guohua2, JIANG Qiaoyong3

1.College of Information and Communication, National University of Defense Technology, Xi’an 710106, China
2.College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
3.School of Computer Science and Engineering, Xi’an University of Technology, Xi’an 710048, China

Online:2018-06-01 Published:2018-06-14

多因子进化算法研究进展

徐庆征1，杨恒1，王娜1，伍国华2，江巧永3

1.国防科技大学信息通信学院，西安 710106
2.国防科技大学系统工程学院，长沙 410073
3.西安理工大学计算机科学与工程学院，西安 710048

Abstract

Abstract: 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.

Key words: multifactorial evolutionary algorithm, multifactorial optimization, evolutionary computation, assortative mating, vertical cultural transmission, memetic algorithm

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。

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

XU Qingzheng1, YANG Heng1, WANG Na1, WU Guohua2, JIANG Qiaoyong3. Recent advances in multifactorial evolutionary algorithm[J]. Computer Engineering and Applications, 2018, 54(11): 15-20.

徐庆征1，杨恒1，王娜1，伍国华2，江巧永3. 多因子进化算法研究进展[J]. 计算机工程与应用, 2018, 54(11): 15-20.

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Recent advances in multifactorial evolutionary algorithm

多因子进化算法研究进展

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