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Mathematical Problems in Engineering
Volume 2013, Article ID 175848, 12 pages
Research Article

Improved Barebones Particle Swarm Optimization with Neighborhood Search and Its Application on Ship Design

College of Shipbuilding Engineering, Harbin Engineering University, Harbin 150001, China

Received 30 August 2012; Revised 17 November 2012; Accepted 25 November 2012

Academic Editor: Baozhen Yao

Copyright © 2013 Jingzheng Yao and Duanfeng Han. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Barebones particle swarm optimization (BPSO) is a new PSO variant, which has shown a good performance on many optimization problems. However, similar to the standard PSO, BPSO also suffers from premature convergence when solving complex optimization problems. In order to improve the performance of BPSO, this paper proposes a new BPSO variant called BPSO with neighborhood search (NSBPSO) to achieve a tradeoff between exploration and exploitation during the search process. Experiments are conducted on twelve benchmark functions and a real-world problem of ship design. Simulation results demonstrate that our approach outperforms the standard PSO, BPSO, and six other improved PSO algorithms.