Modified Backtracking Search Optimization Algorithm Inspired by Simulated Annealing for Constrained Engineering Optimization Problems
Joint Authors
Hu, Zhongbo
Xia, Xuewen
Wang, Hailong
Sun, Yuqiu
Su, Qinghua
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-27, 27 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-02-13
Country of Publication
Egypt
No. of Pages
27
Main Subjects
Abstract EN
The backtracking search optimization algorithm (BSA) is a population-based evolutionary algorithm for numerical optimization problems.
BSA has a powerful global exploration capacity while its local exploitation capability is relatively poor.
This affects the convergence speed of the algorithm.
In this paper, we propose a modified BSA inspired by simulated annealing (BSAISA) to overcome the deficiency of BSA.
In the BSAISA, the amplitude control factor (F) is modified based on the Metropolis criterion in simulated annealing.
The redesigned F could be adaptively decreased as the number of iterations increases and it does not introduce extra parameters.
A self-adaptive ε-constrained method is used to handle the strict constraints.
We compared the performance of the proposed BSAISA with BSA and other well-known algorithms when solving thirteen constrained benchmarks and five engineering design problems.
The simulation results demonstrated that BSAISA is more effective than BSA and more competitive with other well-known algorithms in terms of convergence speed.
American Psychological Association (APA)
Wang, Hailong& Hu, Zhongbo& Sun, Yuqiu& Su, Qinghua& Xia, Xuewen. 2018. Modified Backtracking Search Optimization Algorithm Inspired by Simulated Annealing for Constrained Engineering Optimization Problems. Computational Intelligence and Neuroscience،Vol. 2018, no. 2018, pp.1-27.
https://search.emarefa.net/detail/BIM-1130849
Modern Language Association (MLA)
Wang, Hailong…[et al.]. Modified Backtracking Search Optimization Algorithm Inspired by Simulated Annealing for Constrained Engineering Optimization Problems. Computational Intelligence and Neuroscience No. 2018 (2018), pp.1-27.
https://search.emarefa.net/detail/BIM-1130849
American Medical Association (AMA)
Wang, Hailong& Hu, Zhongbo& Sun, Yuqiu& Su, Qinghua& Xia, Xuewen. Modified Backtracking Search Optimization Algorithm Inspired by Simulated Annealing for Constrained Engineering Optimization Problems. Computational Intelligence and Neuroscience. 2018. Vol. 2018, no. 2018, pp.1-27.
https://search.emarefa.net/detail/BIM-1130849
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1130849