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A novel intelligent global harmony search algorithm based on improved search stability strategy.

Jinglin Wang1, Haibin Ouyang2, Chunliang Zhang1

  • 1School of Mechanical and Electric Engineering, Guangzhou University, Guangzhou, 510006, China.

Scientific Reports
|May 12, 2023
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Summary
This summary is machine-generated.

A new intelligent global harmony search (NIGHS) algorithm improves optimization by enhancing stability and exploration. This novel approach overcomes limitations of traditional harmony search, achieving faster convergence and higher accuracy.

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Area of Science:

  • Computational Intelligence
  • Swarm Intelligence
  • Optimization Algorithms

Background:

  • Harmony Search (HS) is a swarm intelligence algorithm inspired by music improvisation, widely applied in engineering.
  • Existing HS algorithms face challenges like premature convergence, low accuracy, and slow speed in complex problems.

Purpose of the Study:

  • To propose a novel intelligent global harmony search (NIGHS) algorithm to address HS limitations.
  • To enhance search stability, exploration-exploitation balance, and convergence speed.

Main Methods:

  • NIGHS employs an adaptive mean of the harmony memory library to create a stable trust region around the global best harmony.
  • A novel coupling operation based on linear proportional relation adaptively adjusts exploration and exploitation.
  • Dynamic Gauss fine-tuning is integrated within the stable trust region.

Main Results:

  • The NIGHS algorithm demonstrated superior performance on CEC2017 test functions.
  • NIGHS exhibited faster convergence speed compared to standard HS and its improved variants.
  • Improved optimization accuracy was achieved by the NIGHS algorithm.

Conclusions:

  • The proposed NIGHS algorithm effectively overcomes premature convergence and enhances optimization accuracy and speed.
  • NIGHS offers a robust solution for complex optimization problems requiring improved stability and adaptive search capabilities.