Journal
NEURAL COMPUTING & APPLICATIONS
Volume 31, Issue 8, Pages 4385-4405Publisher
SPRINGER LONDON LTD
DOI: 10.1007/s00521-018-3343-2
Keywords
Grasshopper optimization algorithm; Chaotic maps; Global optimization problem; Multimodal function
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Grasshopper optimization algorithm (GOA) is a new meta-heuristic algorithm inspired by the swarming behavior of grasshoppers. The present study introduces chaos theory into the optimization process of GOA so as to accelerate its global convergence speed. The chaotic maps are employed to balance the exploration and exploitation efficiently and the reduction in repulsion/attraction forces between grasshoppers in the optimization process. The proposed chaotic GOA algorithms are benchmarked on thirteen test functions. The results show that the chaotic maps (especially circle map) are able to significantly boost the performance of GOA.
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