Optimum Design of Geodesic Steel Domes Under Code Provisions using Metaheuristic Techniques

Date

2010-06-01

Author

Hasançebi, Oğuzhan
Saka, Mehmet Polat

Metadata

Show full item record

Item Usage Stats

212
views

0
downloads

Metaheuristic search techniques strongly employ randomized decisions while searching for solutions to structural optimization problems. These techniques play an increasingly important role for practically solving hard combinatorial problems from various domains. Over the past few years there has been considerable success in developing metaheuristic search algorithms as well as randomized systematic search methods for obtaining solutions to discrete programming problems. This paper examines minimum weight design of pinjointed geodesic steel domes using seven metaheuristic search techniques; namely, simulated annealing, genetic algorithms, evolution strategies, particle swarm optimizer, tabu search, ant colony optimization and harmony search methods. The optimum design problem of geodesic steel domes is formulated according to design limitations stipulated by ASD-AISC (Allowable Stress Design Code of American Institute of Steel Institution). The minimum design loads and combined load effects are established as specified by ASCE 7-98 (Minimum Design Loads for Buildings and Other Structures, American Society of Civil Engineers). A numerical example is presented, where seven metaheuristic methods are implemented to achieve minimum weight design of a 130member geodesic steel dome subjected to a total of eight combined load cases of dead, live, snow and temperature loads

Subject Keywords

Structural optimization,, Discrete optimization, metaheuristic search techniques, Minimum weight design, Geodesic steel domes

URI

https://hdl.handle.net/11511/79784
https://dergipark.org.tr/tr/pub/ijeas/issue/23574/251119

Journal

International Journal of Engineering and Applied Sciences

Collections

Department of Civil Engineering, Article

Suggestions

OpenMETU
Core

Optimum design of steel frames using stochastic search techniques based on natural phenomena: A review Saka, M. P. (2007-09-21) Recent developments in optimization techniques that deal with finding the solution of combinatorial optimization problems has provided steel designers with new capabilities. These new optimization techniques use nature as a source of inspiration to develop new procedures for solving complex engineering problems. Among these, evolutionary algorithms mimic evolutionary biology and make use of the principle of the survival of the fittest to establish a numerical search algorithm. In the immune system algorithm...
Improving Computational Efficiency of Bat-Inspired Algorithm in Optimal Structural Design Hasançebi, Oğuzhan (2015-07-01) Bat-inspired (BI) algorithm is a recent metaheuristic optimization technique that simulates echolocation behavior of bats in seeking a design space. Along the same line with almost all metaheuristics, this algorithm also entails a large number of time-consuming structural analyses in structural design optimization applications. This study is focused on improving computational efficiency of the BI algorithm in optimum structural design. The number of structural analyses required by BI algorithm in the course...
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...
Adaptive dimensional search: A new metaheuristic algorithm for discrete truss sizing optimization Hasançebi, Oğuzhan (2015-07-01) In the present study a new metaheuristic algorithm called adaptive dimensional search (ADS) is proposed for discrete truss sizing optimization problems. The robustness of the ADS lies in the idea of updating search dimensionality ratio (SDR) parameter online during the search for a rapid and reliable convergence towards the optimum. In addition, several alternative stagnation-control strategies are integrated with the algorithm to escape from local optima, in which a limited uphill (non-improving) move is p...
Performance evaluation of metaheuristic search techniques in the optimum design of real size pin jointed structures Hasançebi, Oğuzhan; Dogan, E.; Erdal, F.; Saka, M. P. (2009-03-01) In recent years a number of metaheuristic search techniques have been widely used in developing structural optimization algorithms. Amongst these techniques are genetic algorithms, simulated annealing, evolution strategies, particle swarm optimizer, tabu search, ant colony optimization and harmony search. The primary goal of this paper is to objectively evaluate the performance of abovementioned seven techniques in optimum design of pin jointed structures. First, a verification of the algorithms used to imp...

Citation Formats

O. Hasançebi and M. P. Saka, “Optimum Design of Geodesic Steel Domes Under Code Provisions using Metaheuristic Techniques,” International Journal of Engineering and Applied Sciences, pp. 88–103, 2010, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/79784.