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A Variable Step Crow Search Algorithm and Its Application in Function Problems.

Yuqi Fan1, Huimin Yang1, Yaping Wang1

  • 1Key Laboratory of Advanced Manufacturing and Intelligent Technology, Ministry of Education, School of Mechanical and Power Engineering, Harbin University of Science and Technology, Harbin 150080, China.

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Summary
This summary is machine-generated.

The Variable Step Crow Search Algorithm (VSCSA) improves optimization by using a cosine function to enhance search abilities and speed. This novel approach boosts population diversity and global searching for superior accuracy.

Keywords:
crow search algorithmoptimization algorithmtest function

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Area of Science:

  • Computational Intelligence
  • Metaheuristic Optimization
  • Swarm Intelligence

Background:

  • Optimization algorithms are crucial for solving complex problems across various fields.
  • The Crow Search Algorithm (CSA) is an efficient metaheuristic inspired by crow behavior.
  • A limitation of CSA is its fixed flight length, potentially leading to local optima.

Purpose of the Study:

  • To introduce a novel optimization algorithm, the Variable Step Crow Search Algorithm (VSCSA).
  • To address the local optimum problem in the standard Crow Search Algorithm.
  • To enhance the performance, convergence speed, and global searching capabilities of CSA.

Main Methods:

  • The proposed VSCSA modifies the Crow Search Algorithm by incorporating a variable step size.
  • A cosine function is utilized to dynamically adjust the search step length.
  • Population diversity and global search capabilities are enhanced through specific update mechanisms.

Main Results:

  • VSCSA demonstrated superior performance across 14 test functions, 2017 CEC functions, and engineering problems.
  • Experimental results showed significant improvements in fitness values, convergence speed, and solution quality.
  • Statistical tests and analysis of searching paths confirmed VSCSA's enhanced global searching ability and accuracy.

Conclusions:

  • The Variable Step Crow Search Algorithm (VSCSA) effectively overcomes the limitations of the standard CSA.
  • VSCSA offers enhanced population diversity, faster convergence, and improved global search capabilities.
  • The proposed algorithm exhibits strong competitiveness and superiority in solving complex optimization problems.