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Neural Computing and Applications

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29-01-2018 | Original Article

Chaotic grasshopper optimization algorithm for global optimization

Authors: Sankalap Arora, Priyanka Anand

Published in: Neural Computing and Applications | Issue 8/2019

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Abstract

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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Title: Chaotic grasshopper optimization algorithm for global optimization
Authors: Sankalap Arora
Priyanka Anand
Publication date: 29-01-2018
Publisher: Springer London
Published in: Neural Computing and Applications / Issue 8/2019
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-018-3343-2

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