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Grasshopper Optimization Algorithm: Theory, Variants, and Applications

Research output: Contribution to journalArticlepeer-review

Abstract

Grasshopper Optimization Algorithm (GOA) is a recent swarm intelligence algorithm inspired by the foraging and swarming behavior of grasshoppers in nature. The GOA algorithm has been successfully applied to solve various optimization problems in several domains and demonstrated its merits in the literature. This paper proposes a comprehensive review of GOA based on more than 120 scientific articles published by leading publishers: IEEE, Springer, Elsevier, IET, Hindawi, and others. It provides the GOA variants, including multi-objective and hybrid variants. It also discusses the main applications of GOA in various fields such as scheduling, economic dispatch, feature selection, load frequency control, distributed generation, wind energy system, and other engineering problems. Finally, the paper provides some possible future research directions in this area.

Original languageEnglish
JournalIEEE Access
DOIs
Publication statusPublished - 2021

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being
  2. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy
  3. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure
  4. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities
  5. SDG 12 - Responsible Consumption and Production
    SDG 12 Responsible Consumption and Production
  6. SDG 13 - Climate Action
    SDG 13 Climate Action
  7. SDG 17 - Partnerships for the Goals
    SDG 17 Partnerships for the Goals

Keywords

  • Economics
  • Education
  • Genetic algorithms
  • GOA
  • Grasshopper Optimization Algorithm
  • Licenses
  • Meta-heuristics
  • MIMICs
  • Optimization
  • Particle swarm optimization
  • Population-based Algorithm
  • Swarm Intelligence

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