Application of a novel metaheuristic algorithm inspired by connected banking system in truss size and layout optimum...

Area of Science:

• Structural Engineering
• Computational Optimization
• Metaheuristic Algorithms

Background:

• Truss structure optimization is complex, especially with mixed continuous and discrete variables for size and layout.
• Metaheuristic algorithms are commonly used, but novel approaches integrating computer network principles are rare.
• Existing methods often require extensive parameter tuning, limiting their practical application.

Purpose of the Study:

• To introduce and evaluate the Connected Banking System Optimizer (CBSO) algorithm for truss optimization.
• To assess the CBSO's performance on benchmark truss size/layout problems and standard test functions.
• To demonstrate the algorithm's robustness and parameter-free nature.

Main Methods:

• Development of the Connected Banking System Optimizer (CBSO) algorithm, inspired by connected banking systems.
• Testing the CBSO on 15, 18, and 25-bar truss structures for size and layout optimization.
• Evaluation using CEC-BC-2017 test functions and other constrained optimization problems.

Main Results:

• The CBSO algorithm achieved superior results compared to existing methods on benchmark truss problems.
• Optimized truss structures designed by CBSO exhibited significantly lighter weights.
• Statistical analyses confirmed the CBSO's efficiency and effectiveness in handling complex optimization tasks.

Conclusions:

• The CBSO is a robust and effective metaheuristic algorithm for truss size and layout optimization.
• Its parameter-free nature simplifies application and enhances its reliability.
• The CBSO offers a promising alternative for structural optimization challenges.