Improved Black-winged Kite Algorithm for Welded Beam Structural Optimization and Cost Management

The design of welded beams needs to consider the balance between structural safety and manufacturing economy, which is a multi-constrained optimization problem. This study proposes an improved strategy for the Black-winged Kite Algorithm (BKA), which uses the Good Point Set (GPS) population initialization and a fitness-driven dynamic selection strategy. The method is applied to the welded beam cost minimization benchmark and compared with other swarm intelligence algorithms. The results show the superiority of the proposed BKA algorithm in calculating the welded beam problem. The optimal design vector satisfies all strength, buckling, and deflection limits. In the future, the improved BKA algorithm will be applied to multi-objective and high-dimensional structural problems.