Modified Atom Search Optimization Based on Immunologic Mechanism and Reinforcement Learning
Joint Authors
Qu, Chiwen
Fu, Yanming
Li, Zhuohang
Chen, Haiqiang
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-22, 22 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-01-14
Country of Publication
Egypt
No. of Pages
22
Main Subjects
Abstract EN
Atom search optimization algorithm has good searching ability and has been successfully applied to calculate hydrogeological parameters and groundwater dispersion coefficient.
Since the atom search optimization algorithm is only based on the atom force motion model in molecular dynamics, it has some shortcomings such as slow search speed and low precision during the later stage of iteration.
A modified atom search optimization based on the immunologic mechanism and reinforcement learning is proposed to overcome the abovementioned shortcomings in this paper.
The proposed algorithm introduces a vaccine operator to better utilize the dominant position in the current atom population so that the speed, accuracy, and domain search ability of the atom search optimization algorithm can be strengthened.
The reinforcement learning operator is applied to dynamically adjust the vaccination probability to balance the global exploration ability and local exploitation ability.
The test results of 21 benchmark functions confirm that the performance of the proposed algorithm is superior to seven contrast algorithms in search accuracy, convergence speed, and robustness.
The proposed algorithm is used to optimize the permutation flow shop scheduling problem.
The experimental results indicate that the proposed algorithm can achieve better optimization results than the seven comparative algorithms, so the proposed algorithm has good practical application value.
American Psychological Association (APA)
Fu, Yanming& Li, Zhuohang& Qu, Chiwen& Chen, Haiqiang. 2020. Modified Atom Search Optimization Based on Immunologic Mechanism and Reinforcement Learning. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-22.
https://search.emarefa.net/detail/BIM-1195245
Modern Language Association (MLA)
Fu, Yanming…[et al.]. Modified Atom Search Optimization Based on Immunologic Mechanism and Reinforcement Learning. Mathematical Problems in Engineering No. 2020 (2020), pp.1-22.
https://search.emarefa.net/detail/BIM-1195245
American Medical Association (AMA)
Fu, Yanming& Li, Zhuohang& Qu, Chiwen& Chen, Haiqiang. Modified Atom Search Optimization Based on Immunologic Mechanism and Reinforcement Learning. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-22.
https://search.emarefa.net/detail/BIM-1195245
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1195245