Quantum-behaved Particle Swarm Optimization for Optimization Design of Steel Structural Element Sections under Axial Compressive Loads

摘要

In the fields of engineering applications, optimal design of structural steel element sections often uses trial method, which search the optima through many times of trial calculation, this method is complex and has a lot of calculation steps, it is very difficult to obtain the global best solution, so it's a tedious and complicated work for technicians. Therefore, particle swarm optimization(PSO) is introduced into structural engineering design, its excellent swarm search ability is utilized to obtain the best optimal section of component. Aiming at the disadvantage of PSO on premature convergence, quantum properties are introduced to improve the traditional PSO, then quantum-behaved PSO(QPSO) is proposed to solve the optimal design of structural steel element sections. The proposed algorithm is used to design the section of axial compression members, optimal design results show that the algorithm is feasible and effective, it also greatly improves the economical performance of section design of steel structural component on condition that meeting the engineering requirements.