Optimum design of steel frames using stochastic search techniques based on natural phenomena: A review

Date

2007-09-21

Author

Saka, M. P.

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

215
views

0
downloads

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 a population of antibodies is evolved to cover a set of antigens as is the case in the vertebrate immune system. Simulated annealing imitates the cooling process of molten metals through annealing. Swarm intelligence is based on the collective behaviour of bird flocking or fish schooling. Ant colony optimization method simulates the social interaction of ant colonies. It has been discovered that ants, while being completely blind, can successfully commute between their nest and food sources by following the shortest path. Ant colony optimization mimics this behaviour of the real ant colony to achieve difficult computations. The harmony search method is based on the musical performance process that takes place when a musician searches for a better state of harmony. Jazz improvisation seeks to find musically pleasing harmony similar to the optimum design process which seeks to find the optimum solution. It became possible through use of these novel techniques to develop structural optimization methods that find the optimum steel sections required for the frame members from the discrete available section lists such that design constraints imposed by design codes are satisfied while the cost or weight of the frame is minimized. This paper firstly introduces the formulation of the steel frame optimization problem where the constraints are implemented from steel design codes. It then reviews the recent structural optimization algorithms that are based on naturally inspired computing methods.

Subject Keywords

Structural optimization, Mathematical programming, Optimality criteria, Combinatorial optimization, Stochastic search techniques, Skeleton structures

URI

https://hdl.handle.net/11511/63863

Collections

Department of Engineering Sciences, Conference / Seminar

Suggestions

OpenMETU
Core

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...
Optimum Design of Geodesic Steel Domes Under Code Provisions using Metaheuristic Techniques Hasançebi, Oğuzhan; Saka, Mehmet Polat (2010-06-01) 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 de...
Metaheuristics in structural optimization and discussions on harmony search algorithm Saka, M. P.; Hasançebi, Oğuzhan; Geem, Z. W. (2016-06-01) Metaheuristic algorithms have provided efficient tools to engineering designers by which it became possible to determine the optimum solutions of engineering design optimization problems encountered in every day practice. Generally metaheuristics are based on metaphors that are taken from nature or some other processes. Because of their success of providing solutions to complex engineering design optimization problems the recent literature has flourished with a large number of new metaheuristics based on a ...
Optimum design of steel sway frames to BS5950 using harmony search algorithm Saka, M. P. (2009-01-01) Harmony search method based optimum design algorithm is presented for the steel sway frames. The harmony search method is a numerical optimization technique developed recently that imitates the musical performance process which takes place when a musician searches for a better state of harmony. Jazz improvisation seeks to find musically pleasing harmony similar to the optimum design process which seeks to find the optimum solution. The optimum design algorithm developed imposes the behavioral and performanc...
An Efficient Metaheuristic Algorithm for Engineering Optimization: SOPT Hasançebi, Oğuzhan (2012-06-01) Metaheuristic algorithms are well-known optimization tools which have been employed for solving a wide range of optimization problems so far. In the present study, a simple optimization (SOPT) algorithm with two main steps; namely exploration and exploitation, is provided for practical applications. Aside from a reasonable rate of convergence attained, the ease in its implementation and dependency on few parameters only are among the advantageous characteristics of the proposed SOPT algorithm. The efficienc...

Citation Formats

M. P. Saka, “Optimum design of steel frames using stochastic search techniques based on natural phenomena: A review,” 2007, p. 105, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/63863.