Hybrid optimization algorithm based on chaos game and differential evolution for constrained optimization of structures

A novel hybrid optimization algorithm, chaos game optimization–differential evolution (CGO-DE), is developed in this study for the size optimization of structures. The key contribution lies in the synergistic combination of chaos game optimization (CGO) and differential evolution (DE), using their respective strengths in exploration and exploitation to effectively identify global optima. The innovative approach independently applies CGO and DE to subpopulations, preventing premature convergence and enhancing overall performance while ensuring accuracy, accounting for design factors and respecting constraints. Comprehensive numerical evaluations on established structural benchmarks (three-bar truss, welded beam and cantilever beam) and large-scale structures (272-bar and 942-bar truss tower) demonstrate the versatility and efficiency of CGO-DE in solving complex optimization problems across various engineering applications. The results underscore the ability of the algorithm to achieve optimal solutions and improve designs compared to other optimization techniques, highlighting its potential as a powerful tool for engineering optimization.