Performance evaluation of metaheuristic search techniques in the optimum design of real size pin jointed structures

2009-03-01
Hasançebi, Oğuzhan
Dogan, E.
Erdal, F.
Saka, M. P.
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 implement the techniques is carried out using a benchmark problem from the literature. Next, the techniques compiled in an unbiased coding platform are evaluated and compared in terms of their solution accuracies as well as convergence rates and reliabilities using four real size design examples formulated according to the design limitations imposed by ASD-AISC (Allowable Stress Design Code of American Institute of Steel Institution). The results reveal that simulated annealing and evolution strategies are the most powerful techniques, and harmony search and simple genetic algorithm methods can be characterized by slow convergence rates and unreliable search performance in large-scale problems.
COMPUTERS & STRUCTURES

Suggestions

Harmony search algorithms in structural engineering
Saka, M.P.; Aydogdu, I.; Hasançebi, Oğuzhan; Geem, Z.W. (2011-08-08)
Harmony search method is widely applied in structural design optimization since its emergence. These applications have shown that harmony search algorithm is robust, effective and reliable optimization method. Within recent years several enhancements are suggested to improve the performance of the algorithm. Among these Mandavi has presented two versions of harmony search methods. He named these as improved harmony search method and global best harmony search method. Saka and Hasancebi (2009) have suggested...
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 the performance of simulated annealing in structural optimization
Hasançebi, Oğuzhan; Saka, Mehmet Polat (2010-03-01)
This study aims at improving the performance of simulated annealing (SA) search technique in real-size structural optimization applications with practical design considerations. It is noted that a standard SA algorithm usually fails to produce acceptable solutions to such problems associated with its poor convergence characteristics and incongruity with theoretical considerations. In the paper novel approaches are developed and incorporated into the standard SA algorithm to eliminate the observed drawbacks ...
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...
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...
Citation Formats
O. Hasançebi, E. Dogan, F. Erdal, and M. P. Saka, “Performance evaluation of metaheuristic search techniques in the optimum design of real size pin jointed structures,” COMPUTERS & STRUCTURES, pp. 284–302, 2009, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/42853.