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Related Experiment Video

Updated: Oct 11, 2025

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Review and analysis for the Red Deer Algorithm.

Raed Abu Zitar1, Laith Abualigah2,3, Nidal A Al-Dmour4

  • 1Sorbonne Center of Artificial Intelligence, Sorbonne University-Abu Dhabi, Abu Dhabi, UAE.

Journal of Ambient Intelligence and Humanized Computing
|November 29, 2021
PubMed
Summary
This summary is machine-generated.

This review details the Red Deer algorithm (RDA), a population-based meta-heuristic. It analyzes RDA

Keywords:
EvolutionaryExploitationMeta-heuristicsProductivityRed Deer Algorithm

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Area of Science:

  • Computational Intelligence
  • Optimization Algorithms

Background:

  • Population-based meta-heuristic algorithms are essential for complex problem-solving.
  • The Red Deer algorithm (RDA) integrates evolutionary principles with heuristic search.

Purpose of the Study:

  • To provide a comprehensive review of the Red Deer algorithm (RDA).
  • To analyze the unique features, weaknesses, and suitable applications of RDA.

Main Methods:

  • Literature review of existing RDA variants and hybrid approaches.
  • Analysis of applications solved using the RDA.

Main Results:

  • Detailed presentation of various RDA implementations and their performance.
  • Identification of strengths and limitations of the RDA.

Conclusions:

  • The Red Deer algorithm offers a unique blend of optimization strategies.
  • Recommendations for future research and application of RDA are provided.