Opposition-Based Barebones Particle Swarm for Constrained Nonlinear Optimization Problems
Author
Source
Mathematical Problems in Engineering
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-08-15
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
This paper presents a modified barebones particle swarm optimization (OBPSO) to solve constrained nonlinear optimization problems.
The proposed approach OBPSO combines barebones particle swarm optimization (BPSO) and opposition-based learning (OBL) to improve the quality of solutions.
A novel boundary search strategy is used to approach the boundary between the feasible and infeasible search region.
Moreover, an adaptive penalty method is employed to handle constraints.
To verify the performance of OBPSO, a set of well-known constrained benchmark functions is used in the experiments.
Simulation results show that our approach achieves a promising performance.
American Psychological Association (APA)
Wang, Hui. 2012. Opposition-Based Barebones Particle Swarm for Constrained Nonlinear Optimization Problems. Mathematical Problems in Engineering،Vol. 2012, no. 2012, pp.1-12.
https://search.emarefa.net/detail/BIM-1001899
Modern Language Association (MLA)
Wang, Hui. Opposition-Based Barebones Particle Swarm for Constrained Nonlinear Optimization Problems. Mathematical Problems in Engineering No. 2012 (2012), pp.1-12.
https://search.emarefa.net/detail/BIM-1001899
American Medical Association (AMA)
Wang, Hui. Opposition-Based Barebones Particle Swarm for Constrained Nonlinear Optimization Problems. Mathematical Problems in Engineering. 2012. Vol. 2012, no. 2012, pp.1-12.
https://search.emarefa.net/detail/BIM-1001899
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1001899