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A Hybrid Lightning Search Algorithm-Simplex Method for Global Optimization
Joint Authors
Zhou, Yongquan
Lu, Yuting
Wu, Xiuli
Source
Discrete Dynamics in Nature and Society
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-23, 23 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-07-13
Country of Publication
Egypt
No. of Pages
23
Main Subjects
Abstract EN
In this paper, a novel hybrid lightning search algorithm-simplex method (LSA-SM) is proposed to solve the shortcomings of lightning search algorithm (LSA) premature convergence and low computational accuracy and it is applied to function optimization and constrained engineering design optimization problems.
The improvement adds two major optimization strategies.
Simplex method (SM) iteratively optimizes the current worst step leaders to avoid the population searching at the edge, thus improving the convergence accuracy and rate of the algorithm.
Elite opposition-based learning (EOBL) increases the diversity of population to avoid the algorithm falling into local optimum.
LSA-SM is tested by 18 benchmark functions and five constrained engineering design problems.
The results show that LSA-SM has higher computational accuracy, faster convergence rate, and stronger stability than other algorithms and can effectively solve the problem of constrained nonlinear optimization in reality.
American Psychological Association (APA)
Lu, Yuting& Zhou, Yongquan& Wu, Xiuli. 2017. A Hybrid Lightning Search Algorithm-Simplex Method for Global Optimization. Discrete Dynamics in Nature and Society،Vol. 2017, no. 2017, pp.1-23.
https://search.emarefa.net/detail/BIM-1151800
Modern Language Association (MLA)
Lu, Yuting…[et al.]. A Hybrid Lightning Search Algorithm-Simplex Method for Global Optimization. Discrete Dynamics in Nature and Society No. 2017 (2017), pp.1-23.
https://search.emarefa.net/detail/BIM-1151800
American Medical Association (AMA)
Lu, Yuting& Zhou, Yongquan& Wu, Xiuli. A Hybrid Lightning Search Algorithm-Simplex Method for Global Optimization. Discrete Dynamics in Nature and Society. 2017. Vol. 2017, no. 2017, pp.1-23.
https://search.emarefa.net/detail/BIM-1151800
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1151800