Improving Computational Efficiency of Particle Swarm Optimization for Optimal Structural Design

Date

2013-06-01

Author

Hasançebi, Oğuzhan

Metadata

Show full item record

Item Usage Stats

203
views

0
downloads

This paper attempts to improve the computational efficiency of the well known particle swarm optimization (PSO) algorithm for tackling discrete sizing optimization problems of steel frame structures. It is generally known that, in structural design optimization applications, PSO entails enormously time-consuming structural analyses to locate an optimum solution. Hence, in the present study it is attempted to lessen the computational effort of the algorithm, using the so called upper bound strategy (UBS), which is a recently proposed strategy for reducing the total number of structural analyses involved in the course of design optimization. In the UBS, the key issue is to identify those candidate solutions which have no chance to improve the search during the optimum design process. After identifying those non-improving solutions, they are directly excluded from the structural analysis stage, diminishing the total computational cost. The performance of the UBS integrated PSO algorithm (UPSO) is evaluated in discrete sizing optimization of a real scale steel frame to AISC-LRFD specifications. The numerical results demonstrate that the UPSO outperforms the original PSO algorithm in terms of the computational efficiency.

URI

https://hdl.handle.net/11511/80053
http://ijoce.iust.ac.ir/browse.php?mag_id=13&&slc_lang=en&sid=1

Journal

International Journal of Optimization in Civil Engineering

Collections

Department of Civil Engineering, Article

Suggestions

OpenMETU
Core

Improving the big bang-big crunch algorithm for optimum design of steel frames Hasançebi, Oğuzhan (null; 2012-01-01) This paper presents an improved version of the big bang-big crunch (BB-BC) algorithm namely exponential BB-BC algorithm (EBB-BC) for optimum design of steel frames according to ASD-AISC provisions. It is shown that the standard version of the algorithm sometimes is unable to provide reasonable solutions for problems from discrete design optimization of steel frames. Therefore, by investigating the shortcomings of the BB-BC algorithm, it is aimed to enhance the algorithm for solving complicated steel frame o...
Optimum design of unbraced steel frames to LRFD-AISC using particle swarm optimization Dogan, E.; Saka, M. P. (2012-04-01) Particle Swarm method based optimum design algorithm for unbraced steel frames is presented. The Particle Swarm method is a numerical optimization technique that simulates the social behavior of birds, fishes and bugs. In nature fish school, birds flock and bugs swarm not only for reproduction but for other reasons such as finding food and escaping predators. Similar to birds seek to find food, the optimum design process seeks to find the optimum solution. In the particle swarm optimization each particle in...
Optimal load and resistance factor design of geometrically nonlinear steel space frames via tabu search and genetic algorithm DEĞERTEKİN, SADIK ÖZGÜR; Saka, M. P.; HAYALİOĞLU, MEHMET SEDAT (Elsevier BV, 2008-01-01) In this paper, algorithms are presented for the optimum design of geometrically nonlinear steel space frames using tabu search and genetic algorithm. Tabu search utilizes the features of short-term memory facility (tabu list) and aspiration criteria. Genetic algorithm employs reproduction, crossover and mutation operators. The design algorithms obtain minimum weight frames by selecting suitable sections from a standard set of steel sections such as American Institute of Steel Construction (AISC) wide-flange...
Implicit monolithic parallel solution algorithm for seismic analysis of dam-reservoir systems Özmen, Semih; Kurç, Özgür; Department of Civil Engineering (2016) This research mainly focuses on developing a computationally scalable and efficient solution algorithm that can handle linear dynamic analysis of dam-reservoir interaction problem. Lagrangian fluid finite elements are utilized and compressibility and viscosity of the fluid are taken into consideration during the reservoir modeling. In order to provide computational scalability and efficiency, domain decomposition methods implemented with parallel computing approaches such as Finite Element Tearing and Inter...
Rigorous Analysis of Deformed Nanowires Using the Multilevel Fast Multipole Algorithm Karaosmanoglu, Bariscan; Yilmaz, Akif; Ergül, Özgür Salih (2015-05-17) We present accurate full-wave analysis of deformed nanowires using a rigorous simulation environment based on the multilevel fast multipole algorithm. Single nanowires as well as their arrays are deformed randomly in order to understand the effects of deformations to scattering characteristics of these structures. Results of hundreds of simulations are considered for statistically meaningful analysis of deformation effects. We show that deformations significantly enhance the forward-scattering abilities of ...

Citation Formats

O. Hasançebi, “Improving Computational Efficiency of Particle Swarm Optimization for Optimal Structural Design,” International Journal of Optimization in Civil Engineering, pp. 563–574, 2013, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/80053.