Journal
JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS
Volume 21, Issue 2, Pages 300-311Publisher
SYSTEMS ENGINEERING & ELECTRONICS, EDITORIAL DEPT
DOI: 10.3969/j.issn.1004-4132.2010.02.021
Keywords
swarm intelligence; global optimization; human searching behaviors; seeker optimization algorithm
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Funding
- National Natural Science Foundation of China [60870004]
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A novel heuristic search algorithm called seeker optimization algorithm (SOA) is proposed for the real-parameter optimization. The proposed SOA is based on simulating the act of human searching. In the SOA, search direction is based on empirical gradients by evaluating the response to the position changes, while step length is based on uncertainty reasoning by using a simple fuzzy rule. The effectiveness of the SOA is evaluated by using a challenging set of typically complex functions in comparison to differential evolution (DE) and three modified particle swarm optimization (PSO) algorithms. The simulation results show that the performance of the SOA is superior or comparable to that of the other algorithms.
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