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A comprehensive database of Nature-Inspired Algorithms.

Alexandros Tzanetos1, Iztok Fister2, Georgios Dounias1

  • 1Management and Decision Engineering Laboratory, Department of Financial and Management Engineering, School of Engineering, University of the Aegean, Greece.

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Summary
This summary is machine-generated.

This study presents a comprehensive collection of Nature-Inspired Algorithms (NIAs) to aid researchers. It offers a structured taxonomy and application insights for these rapidly evolving computational methods.

Keywords:
Bio-inspired algorithmsEvolutionary algorithmsEvolutionary computingNature-inspired algorithmsNature-inspired computingSwarm intelligence

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Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Optimization Techniques

Background:

  • The proliferation of Nature-Inspired Algorithms (NIAs) presents a challenge for researchers seeking to stay current.
  • A lack of standardized classification hinders understanding and application of NIAs.
  • Existing literature lacks a consolidated overview of published NIAs.

Purpose of the Study:

  • To compile a comprehensive dataset of all published Nature-Inspired Algorithms.
  • To develop a robust taxonomy for classifying NIAs based on their features.
  • To provide insights into the application domains of various NIAs.

Main Methods:

  • Conducted two extensive surveys to gather data on published Nature-Inspired Algorithms.
  • Collected preliminary data on algorithm characteristics and publication status.
  • Analyzed and categorized algorithms based on identified features for taxonomic development.

Main Results:

  • A comprehensive collection of Nature-Inspired Algorithms is presented.
  • A novel taxonomy is proposed, categorizing algorithms by specific features.
  • Insights into the diverse application areas addressed by NIAs are provided.

Conclusions:

  • The compiled data and taxonomy offer a valuable resource for researchers in the field of Nature-Inspired Algorithms.
  • This work facilitates a better understanding of the NIA landscape and their practical utility.
  • The structured collection aids in navigating the growing number of nature-inspired computational approaches.