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Slime Mould Algorithm: A Comprehensive Survey of Its Variants and Applications.

Farhad Soleimanian Gharehchopogh1, Alaettin Ucan2, Turgay Ibrikci3

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The Slime Mould Algorithm (SMA) is a novel meta-heuristic algorithm inspired by nature, offering optimal solutions for complex optimization problems. Research shows its increasing application in hybridization, progress, changes, and optimization tasks.

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Area of Science:

  • Engineering and Computer Science
  • Optimization Techniques
  • Computational Intelligence

Background:

  • Meta-heuristic algorithms are crucial for solving complex optimization problems in science and engineering.
  • The Slime Mould Algorithm (SMA) is a recently developed meta-heuristic algorithm inspired by the foraging behavior of slime mold.
  • SMA features a unique mathematical model simulating biological wave-like movement for efficient exploration and exploitation.

Purpose of the Study:

  • To investigate the Slime Mould Algorithm (SMA) from various optimization perspectives.
  • To analyze the hybridization, progress, changes, and optimization applications of SMA.
  • To provide a comprehensive overview of SMA's utility for researchers and practitioners.

Main Methods:

  • Review and analysis of existing research on the Slime Mould Algorithm (SMA).
  • Categorization of SMA applications into hybridization, progress, changes, and optimization.
  • Quantitative assessment of SMA's usage rates in these four areas.

Main Results:

  • The Slime Mould Algorithm (SMA) demonstrates significant potential in addressing optimization challenges.
  • SMA has been increasingly adopted in scientific research, with applications in hybridization (15%), progress (36%), changes (7%), and optimization (42%).
  • The algorithm's unique features, including adaptive weights and a biological wave simulation, contribute to its effectiveness.

Conclusions:

  • The Slime Mould Algorithm (SMA) is a valuable and versatile meta-heuristic tool for optimization problems.
  • Its unique approach and growing body of research suggest continued relevance and application in engineering and scientific fields.
  • This paper serves as a beneficial resource for engineers, professionals, and academic scientists utilizing or exploring SMA.