Solving Structural Optimization Problem Using Bare-Bones Particle Swarm Optimization  

Oleh:

Wibowo, D. K. ; Cheng, M-Y. ; Prayogo, D.

Jenis: Article from Proceeding
Dalam koleksi: Proceeding The 1st International Conference on Sustainable Civil Engineering Structures and Construction Materials (SCESCM) di Yogyakarta, September 11 – 13, 2012, page 82-89.
Topik: Bare-bones PSO; Structural optimization; Metaheuristic.
Fulltext: 10.pdf (521.59KB)

Isi artikel

In many practical applications of structural optimization, most problems are highly nonlinear due to a huge number of design variables and complex constraints on stresses, displacements, load carrying capability, and geometrical configuration. As a result, finding the optimal solution becomes an uneasy task and extremely challenging. The traditional local search algorithms, such as Nelder-Mead downhill methods, hill-climbing, and steepest descent, are often failed to search the optimum solution in nonlinear problem. In this study, a metaheuristic approach, namely bare-bones PSO (BBPSO), is introduced to solve a set of complex structural optimization problems. BBPSO is a variant of the particle swarm optimization in which the velocity and position-update rules are replaced with samples from Gaussian distribution. To validate the performance of BBPSO, several case studies of structural optimization problem are provided, including truss design, reinforce concrete beam design, and tubular column design. The results indicate the potential of BBPSO as an alternative approach to solve many structural optimization problems.

Opini Anda

Klik untuk menuliskan opini Anda tentang koleksi ini!

Kembali