Comparative Study on Recent Metaheuristic Algorithms in Design Optimization of Cold-Formed Steel Structures

2015 ◽  
pp. 145-173 ◽  
Author(s):  
M. P. Saka ◽  
S. Carbas ◽  
I. Aydogdu ◽  
A. Akin ◽  
Z. W. Geem
Keyword(s):  
Comparative Study ◽  
Design Optimization ◽  
Steel Structures ◽  
Metaheuristic Algorithms ◽  
Cold Formed Steel

Design Optimization of a Special Class of Steel Structures via Genetic Algorithms and Stochastic Sampling

2009 ◽  
Author(s):  
Karim Hamza ◽  
Ashraf O. Nassef ◽  
Mohammed Shalaby
Keyword(s):  
Genetic Algorithms ◽  
Design Optimization ◽  
Special Class ◽  
Steel Structures ◽  
Sampling Technique ◽  
Manufacturing Cost ◽  
Stochastic Sampling ◽  
Optimization Task ◽  
Consistent Performance ◽  
Continuous And Discrete Variables

This paper addresses the design optimization of a special class of steel structures, which is clear-span building built up via off-shelf standard steel-sections. The problem is of particular importance in small to medium span buildings due to an attractive opportunity for reduction of the manufacturing cost compared to trusses and custom-built beams. The problem is also difficult from an optimization perspective as it exhibits both continuous and discrete variables, as well as discontinuities and flat regions in the topology of the objective function. Genetic algorithms (GA) and a special stochastic sampling technique are considered for the problem, as well as a mixed GA and stochastic sampling approach. The stochastic sampling is guided via heuristic rules based on knowledge specific to the problem, and is thus perceived well suited to the optimization task. While all the tested algorithms produced satisfactory results, the mixed approach seemed to yield the most consistent performance.

Design optimisation for cold-formed steel residential roof truss using genetic algorithm

2018 ◽  
Vol 15 (5) ◽  
pp. 575-583
Author(s):  
Ka Yee Kok ◽  
Hieng Ho Lau ◽  
Thanh Duoc Phan ◽  
TIina Chui Huon Ting
Keyword(s):  
Genetic Algorithm ◽  
Industrial Application ◽  
Steel Structures ◽  
Single Type ◽  
Efficient Design ◽  
Design Optimisation ◽  
Content Type ◽  
Roof Truss ◽  
Cold Formed Steel ◽  
Multi Level

Purpose This paper aims to present the design optimisation using genetic algorithm (GA) to achieve the highest strength to weight (S/W) ratio, for cold-formed steel residential roof truss. Design/methodology/approach The GA developed in this research simultaneously optimises roof pitch, truss configurations, joint coordinates and applied loading of typical dual-pitched symmetrical residential roof truss. The residential roof truss was considered with incremental uniform distributed loading, in both gravitational and uplift directions. The structural analyses of trusses were executed in this GA using finite element toolbox. The ultimate strength and serviceability of trusses were checked through the design formulation implemented in GA, according to the Australian standard, AS/NZS 4600 Cold-formed Steel Structures. Findings An optimum double-Fink roof truss which possess highest S/W ratio using GA was determined, with optimum roof pitch of 15°. The optimised roof truss is suitable for industrial application with its higher S/W ratio and cost-effectiveness. The combined methodology of multi-level optimisation and simultaneous optimisation developed in this research could determine optimum roof truss with consistent S/W ratio, although with huge GA search space. Research limitations/implications The sizing of roof truss member is not optimised in this paper. Only single type of cold-formed steel section is used throughout the whole optimisation. The design of truss connection is not considered in this paper. The corresponding connection costs are not included in the proposed optimisation. Practical implications The optimum roof truss presented in this paper is suitable for industrial application with higher S/W ratio and lower cost, in either gravitational or uplift loading configurations. Originality/value This research demonstrates the approaches in combining multi-level optimisation and simultaneous optimisation to handle large number of variables and hence executed an efficient design optimisation. The GA designed in this research determines the optimum residential roof truss with highest S/W ratio, instead of lightest truss weight in previous studies.

scholarly journals Multiobjective optimal design of reinforced concrete frames using two metaheuristic algorithms

2021 ◽  
Vol 9 (4B) ◽  
Author(s):  
Mehdi Babaei ◽  
◽  
Masoud Mollayi ◽  
Keyword(s):  
Reinforced Concrete ◽  
Optimal Design ◽  
Optimization Problem ◽  
Numerical Models ◽  
Steel Structures ◽  
Metaheuristic Algorithms ◽  
Rc Structures ◽  
Weighted Sum Method ◽  
Rc Frames ◽  
Single Objective

Genetic algorithm (GA) and differential evolution (DE) are metaheuristic algorithms that have shown a favorable performance in the optimization of complex problems. In recent years, only GA has been widely used for single-objective optimal design of reinforced concrete (RC) structures; however, it has been applied for multiobjective optimization of steel structures. In this article, the total structural cost and the roof displacement are considered as objective functions for the optimal design of the RC frames. Using the weighted sum method (WSM) approach, the two-objective optimization problem is converted to a single-objective optimization problem. The size of the beams and columns are considered as design variables, and the design requirements of the ACI-318 are employed as constraints. Five numerical models are studied to test the efficiency of the GA and DE algorithms. Pareto front curves are obtained for the building models using both algorithms. The detailed results show the accuracy and convergence speed of the algorithms.

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