การผสมผสานของวิธีฝูงอนุภาคกับวิธีเชิงพันธุกรรมและวิธีจำลองการหล่ออบเหนียวสำหรับออกแบบที่เหมาะสมของโครงสร้างคอนกรีตเสริมเหล็ก

บทคัดย่อ

This research introduces the hybridization of a particle swarm optimization with genetic algorithm and simulated annealing algorithm for solving optimum design of reinforced concrete structures. The objective function is the total cost of reinforced concrete structure. Hybrid particle swarm optimization is developed and evaluated the design results according to ACI318-08. Then, the performances of hybrid particle swarm optimization are demonstrated by statistical results from different reinforced concrete structure design examples. From the results showed that, the hybrid particle swarm optimization can be used to design an appropriate reinforced concrete structures effectively which obtains the best economical design results and the better statistical results than that of the particle swarm optimization for all design examples. In addition, the optimum solutions have saving cost than the related literature for all examples.