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| Parameter Settings Analysis for Glowworm Swarm Optimization Algorithm |
| Heng Zhang, Ping Fu, Yanli Liu |
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Abstract Glowworm Swarm Optimization (GSO) algorithm is a new swarm
intelligence optimization method at present, which is initially used
to solve the multi-modal function optimization problem. In order to
deeply make use of the merits of GSO algorithm in more extensive
areas, this paper analyzes the impact of parameter settings on the
performance of GSO algorithm, and then ranks the impact factors by
the Likert scale positive evaluation weighted average method.
According to the simulation experiments, it can be concluded that
the value of the movement step is the most important factor.
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