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A comprehensive survey of the Grasshopper optimization algorithm: results, variants, and applications

Abstract

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.

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Correspondence to Laith Abualigah.

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Abualigah, L., Diabat, A. A comprehensive survey of the Grasshopper optimization algorithm: results, variants, and applications. Neural Comput & Applic 32, 15533–15556 (2020). https://doi.org/10.1007/s00521-020-04789-8

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Keywords

  • Grasshopper optimization algorithm
  • Meta-heuristic optimization algorithms
  • Optimization problems
  • Bio-inspired algorithms