Research Area: Metaheuristic Computing
The grasshopper optimization algorithm is one of the dominant modern meta-heuristic optimization algorithms. It has been successfully applied to various optimization problems in several fields, including engineering design, wireless networking, machine learning, image processing, control of power systems, and others. We survey the available literature on the grasshopper optimization algorithm, including its modifications, hybridizations, and generalization to the binary, chaotic, and multi-objective cases. We review its applications, evaluate the algorithms, and provide conclusions.
Keywords:
grasshopper
metaheuristic optimization algorithm
engineering design
wireless networking
machine learning
image processing
control of power systems
binary
chaotic
multi-objective optimization
Author(s) Name: Laith Abualigah, Ali Diabat
Journal name: Neural Computing and Applications
Conferrence name:
Publisher name: Springer
DOI: 10.1007/s00521-020-04789-8
Volume Information: 32, pages 15533–15556
