Truss-sizing optimization attempts with CSA: a detailed evaluation
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METHODOLOGIES AND APPLICATION
Truss-sizing optimization attempts with CSA: a detailed evaluation Hakan Ozbasaran1 • Meltem Eryilmaz Yildirim1
Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Thanks to the advent of powerful computers, searching for optimal solutions to engineering design problems becomes easier every day. Numerous researchers are still developing modern optimization algorithms, and the competition for ‘‘the most efficient optimization algorithm’’ continues apace. This study evaluates the performances of the Crow Search Algorithm (CSA) and a slightly modified variant (CSAM) in one of the most popular and controversial competitions in the structural optimization field for the first time. Unlike most of the works on structural optimization, this paper does not tell a success story. After days of computation to collect the sensitivity and convergence data, it is shown that both CSA and CSAM mostly fail compared to today’s competitive algorithms. The findings of the study are discussed through tables and plots in detail to share the unfavorable experience on the truss optimization attempts, to review the difficulties of using parameter-controlled algorithms in structural optimization through CSA, and to save time for the researchers in the field. Keywords Truss Size optimization Metaheuristics CSA Parameter tuning
1 Introduction It is worth remembering the quote from the great mathematician and physicist Leonhard Euler at the beginning of the introduction: Nothing at all takes place in the universe in which some rule of maximum or minimum does not appear. The species adapt and change by natural selection to become more ‘‘fit’’ to survive according to the well-known evolution theory. Depending on the survival characteristics of the species and environmental conditions, the measure of fitness can be how fast the creature runs or how poisonous is the creature, etc. The life forms are evolving in every generation and trying to be more fit biologically. Searching for the optimal (fittest) solutions for the problems that we encounter is our nature.
Communicated by V. Loia. & Meltem Eryilmaz Yildirim [email protected] Hakan Ozbasaran [email protected] 1
Department of Civil Engineering, Eskisehir Osmangazi University, Eskisehir, Turkey
Size optimization of a skeletal structure is to determine the best sections for the member groups of a given configuration under the considered constraints such as stress, displacement, buckling, and frequency. The measure that defines ‘‘the optimum’’ is the cost in most of the engineering design problems. Although cost is the total of structural material, labor, equipment rental, site running, etc., expenses, mostly, the amount of the structural material used solely is defined as the objective value. Since the objective functions of the most structural optimization problems are computationally expensive, harvesting satisfactory results from optimization attempts of engineering structures has h
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