Fractional-Order Boosted Hybrid Young's Double-Slit Experimental Optimizer for Truss Topology Engineering...

Area of Science:

• Computational Intelligence
• Meta-heuristic Optimization
• Physics-Inspired Algorithms

Background:

• Young's Double-Slit Experiment (YDSE) optimization algorithm is a physics-driven meta-heuristic with unique search properties.
• YDSE faces challenges in complex, high-dimensional problems, exhibiting slow convergence and local optima entrapment.

Purpose of the Study:

• To propose a novel fractional-order boosted hybrid YDSE (FYDSE) to address the limitations of the original YDSE.
• To enhance the convergence rate, global search capability, and robustness of the YDSE optimizer for complex optimization tasks.

Main Methods:

• Introduced a fractional-order strategy in dark edge position updates for efficient neighborhood search and reduced local optima entrapment.
• Implemented piecewise chaotic mapping for better initial population distribution and faster convergence.
• Utilized a dynamic opposition strategy to expand exploration space and improve global optimum acquisition.
• Incorporated a vertical operator to balance global exploration and local exploitation.

Main Results:

• FYDSE demonstrated superior performance over the standard YDSE in 91.6% of cec2022 benchmark test functions.
• FYDSE achieved the best performance among all compared algorithms in 66.6% of the tests.
• FYDSE obtained optimal best and average weights for truss structure optimization problems (20-bar, 24-bar, 72-bar), proving its efficacy on difficult cases.

Conclusions:

• The proposed FYDSE effectively enhances the optimization capabilities of the YDSE algorithm.
• FYDSE shows significant improvements in convergence speed, global search, and handling complex optimization problems.
• FYDSE offers a promising approach for tackling challenging optimization tasks in various domains.