A simplified group search optimizer algorithm denoted as “SGSO” for large scale global optimization
is presented in this paper to obtain a simple algorithm with superior performance on high-dimensional problems.
The SGSO adopts an improved sharing strategy which shares information of not only the best member but also the
other good members, and uses a simpler search method instead of searching by the head angle. Furthermore, the
SGSO increases the percentage of scroungers to accelerate convergence speed. Compared with genetic algorithm
(GA), particle swarm optimizer (PSO) and group search optimizer (GSO), SGSO is tested on seven benchmark
functions with dimensions 30, 100, 500 and 1 000. It can be concluded that the SGSO has a remarkably superior
performance to GA, PSO and GSO for large scale global optimization.
ZHANG Wen-fen (张雯雰)
. Simplified Group Search Optimizer Algorithm for Large Scale Global Optimization[J]. Journal of Shanghai Jiaotong University(Science), 2015
, 20(1)
: 38
-43
.
DOI: 10.1007/s12204-015-1585-z
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