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Multi scenario chaotic transient search optimization algorithm for global optimization technique.

Ibrahim Mohamed Diaaeldin1, Hany M Hasanien2,3, Mohammed H Qais4

  • 1Engineering Physics and Mathematics Department, Faculty of Engineering, Ain Shams University, Abbassia, Cairo, 11517, Egypt.

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Summary
This summary is machine-generated.

The new chaotic transient search optimization (CTSO) algorithm uses chaotic maps to enhance optimization, effectively solving complex engineering problems and outperforming existing methods.

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Area of Science:

  • Computational Intelligence
  • Engineering Optimization
  • Metaheuristic Algorithms

Background:

  • Chaotic maps (CMs) are increasingly used in optimization to overcome local optima in non-convex problems.
  • Transient Search Optimization (TSO) is a physics-based metaheuristic algorithm.

Purpose of the Study:

  • To develop a novel Chaotic Transient Search Optimization (CTSO) algorithm.
  • To enhance the search capabilities of the TSO algorithm using chaotic maps.
  • To evaluate CTSO's performance on benchmark functions and real-world engineering problems.

Main Methods:

  • Integration of nine chaotic maps into the TSO algorithm.
  • Testing CTSO on 23 uni- and multi-modal benchmark functions.
  • Comparative analysis with the original TSO using statistical tests (Wilcoxon, sign, t-test) and performance metrics (convergence, time).
  • Application of CTSO to engineering design problems: coil spring, welded beam, and pressure vessel.

Main Results:

  • CTSO demonstrated improved search capabilities compared to the original TSO.
  • Statistical tests confirmed the significant performance enhancement of CTSO.
  • CTSO achieved superior results in solving real-life engineering design problems.
  • The integration of chaotic maps effectively improved TSO's random number generation and search efficiency.

Conclusions:

  • The proposed Chaotic Transient Search Optimization (CTSO) algorithm is a robust and effective metaheuristic for complex optimization tasks.
  • CTSO offers a significant improvement over the standard TSO, particularly for non-convex and real-world engineering problems.
  • The use of chaotic maps is a viable strategy for enhancing the performance of physics-based optimization algorithms.