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

Laith Abualigah, Ali Diabat

Research output: Contribution to journalReview articlepeer-review

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.

Original languageEnglish (US)
Pages (from-to)15533-15556
Number of pages24
JournalNeural Computing and Applications
Volume32
Issue number19
DOIs
StatePublished - Oct 1 2020

Keywords

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

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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