Pigeon-inspired optimization: a new swarm intelligence optimizer for air robot path planning
International Journal of Intelligent Computing and Cybernetics
ISSN: 1756-378X
Article publication date: 4 March 2014
Abstract
Purpose
The purpose of this paper is to present a novel swarm intelligence optimizer — pigeon-inspired optimization (PIO) — and describe how this algorithm was applied to solve air robot path planning problems.
Design/methodology/approach
The formulation of threat resources and objective function in air robot path planning is given. The mathematical model and detailed implementation process of PIO is presented. Comparative experiments with standard differential evolution (DE) algorithm are also conducted.
Findings
The feasibility, effectiveness and robustness of the proposed PIO algorithm are shown by a series of comparative experiments with standard DE algorithm. The computational results also show that the proposed PIO algorithm can effectively improve the convergence speed, and the superiority of global search is also verified in various cases.
Originality/value
In this paper, the authors first presented a PIO algorithm. In this newly presented algorithm, map and compass operator model is presented based on magnetic field and sun, while landmark operator model is designed based on landmarks. The authors also applied this newly proposed PIO algorithm for solving air robot path planning problems.
Keywords
Acknowledgements
This work was partially supported by Natural Science Foundation of China (NSFC) under grant no. 61333004, no. 61273054 and no. 60975072, National Key Basic Research Program of China (973 Project) under grant no. 2014CB046401, Top-Notch Young Talents Program of China, and Aeronautical Foundation of China under grant no. 20135851042.
Citation
Duan, H. and Qiao, P. (2014), "Pigeon-inspired optimization: a new swarm intelligence optimizer for air robot path planning", International Journal of Intelligent Computing and Cybernetics, Vol. 7 No. 1, pp. 24-37. https://doi.org/10.1108/IJICC-02-2014-0005
Publisher
:Emerald Group Publishing Limited
Copyright © 2014, Emerald Group Publishing Limited