Improved Laplacian Biogeography-Based Optimization Algorithm and Its Application to QAP
Joint Authors
Zhang, Xinming
Wang, Doudou
Chen, Haiyan
Mao, Wentao
Liu, Shangwang
Liu, Guoqi
Dou, Zhi
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-19, 19 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-04-06
Country of Publication
Egypt
No. of Pages
19
Main Subjects
Abstract EN
Laplacian Biogeography-Based Optimization (LxBBO) is a BBO variant which improves BBO’s performance largely.
When it solves some complex problems, however, it has some drawbacks such as poor performance, weak operability, and high complexity, so an improved LxBBO (ILxBBO) is proposed.
First, a two-global-best guiding operator is created for guiding the worst habitat mainly to enhance the exploitation of LxBBO.
Second, a dynamic two-differential perturbing operator is proposed for the first two best habitats’ updating to improve the global search ability in the early search phase and the local one in the late search one, respectively.
Third, an improved Laplace migration operator is formulated for other habitats’ updating to improve the search ability and the operability.
Finally, some measures such as example learning, mutation operation removing, and greedy selection are adopted mostly to reduce the computation complexity of LxBBO.
A lot of experimental results on the complex functions from the CEC-2013 test set show ILxBBO obtains better performance than LxBBO and quite a few state-of-the-art algorithms do.
Also, the results on Quadratic Assignment Problems (QAPs) show that ILxBBO is more competitive compared with LxBBO, Improved Particle Swarm Optimization (IPSO), and Improved Firefly Algorithm (IFA).
American Psychological Association (APA)
Zhang, Xinming& Wang, Doudou& Chen, Haiyan& Mao, Wentao& Liu, Shangwang& Liu, Guoqi…[et al.]. 2020. Improved Laplacian Biogeography-Based Optimization Algorithm and Its Application to QAP. Complexity،Vol. 2020, no. 2020, pp.1-19.
https://search.emarefa.net/detail/BIM-1143909
Modern Language Association (MLA)
Zhang, Xinming…[et al.]. Improved Laplacian Biogeography-Based Optimization Algorithm and Its Application to QAP. Complexity No. 2020 (2020), pp.1-19.
https://search.emarefa.net/detail/BIM-1143909
American Medical Association (AMA)
Zhang, Xinming& Wang, Doudou& Chen, Haiyan& Mao, Wentao& Liu, Shangwang& Liu, Guoqi…[et al.]. Improved Laplacian Biogeography-Based Optimization Algorithm and Its Application to QAP. Complexity. 2020. Vol. 2020, no. 2020, pp.1-19.
https://search.emarefa.net/detail/BIM-1143909
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1143909