Optimum design of post‐tensioned axially symmetric cylindrical walls using novel hybrid metaheuristic methods

Abstract

An efficient methodology for various structural design problems is needed to optimize the total cost for structures. Although some methods seem to be efficient for applications, due to using special algorithm parameters, computational cost, and some other reasons, there is still much to be done in order to develop an effective method for general design applications. This paper describes the influence of the selected procedure on the design of cost-optimized, post-tensioned axially symmetric cylindrical reinforced concrete walls. In this study, the optimum design of axially symmetric cylindrical walls using several metaheuristic algorithms is investigated. The new generation algorithms used in the study are flower pollination algorithm, teaching-learning-based optimization, and Jaya algorithm (JA). These algorithms are also compared with one of the previously developed algorithm called harmony search. The numerical examples were done for walls with 4-to 10-m height and for 1, 5, 10, 15, 20, and 25 post-tensioned load cases, respectively. Several independent runs are conducted, and in some of these runs, JA may trap to a local solution. To overcome this situation, hybrid algorithms such as JA using Lévy flights, JA using Lévy flights with probabilistic student phase (JALS), JA using Lévy Flights with consequent student phase (JALS2), and JA with probabilistic student phase are developed. It is seen that in many respects, the JALS2 and JALS are the most effective within the proposed hybrid approaches. KEYWORDS cost optimization cylindrical walls, flower pollination algorithm, hybrid algorithm analyses of cylindrical walls, Jaya algorithm, teaching-learning-based optimization 1 | INTRODUCTION Engineering designs are based on two main objectives. These two objectives, defined as safety and cost, are two opposing concepts, when one is increasing, the other one is decreasing. If all parameters belonging to these two purposes are formulated, it may be possible to obtain a solution that simultaneously provides these two goals with mathematical operations. This may not be always possible or easy task in some cases such as design of structural systems, in which many parameters affect each other. For four decades, metaheuristic algorithms have been widely used to perform this task. The most important reason why algorithms are used so widely is that not only the ability of solving problems that are difficult or impossible to express mathematically but also easily applying of these algorithms to the problems without using complex mathematical functions.From the first day to the present, a considerable number of metaheuristic algorithm has been proposed. Looking at the number of algorithms, it brings out questions such as what the reason is, why so many algorithms are proposed, are the algorithms insufficient to achieve the optimization task, if so, why more algorithms are suggested, and if algorithms are successful what is the measure of success. These questions can be further diversified. The answer to these questions can be ...

Game theory‐based metaheuristics for structural design optimization

“…It has only one movement mechanism, and there is no hyperparameter; therefore, parameter tuning is not needed. Second, Jaya algorithm obtains satisfactory and competitive results in constrained design problems (Bekdaş, 2019; Brajević & Ignjatović, 2019; Rao & Waghmare, 2017). In a Jaya algorithm, search agents try to approach to the optimal solution.…”

Optimum design of timber structures under fire using metaheuristic algorithm

“…The existing or new-generation metaheuristic algorithms are widely used in various structural engineering applications, such as in thin-wall structures, cantilever retaining walls, structural control devices (passive, active or base isolation), and the steel and reinforced-concrete structural elements. An optimum design of post-tensioned axially symmetric cylindrical reinforced concrete walls using the harmony search algorithm [10] and novel hybrid metaheuristic methods (Jaya using Lévy flights, Jaya using Lévy flights with probabilistic student phase (JALS), JA using Lévy Flights with consequent student phase (JALS2)), with different height and load cases [11], and the design of cantilever soldier pile retaining walls via the harmony search algorithm [12], are some examples of the use of such algorithms in thin-wall and cantilever retaining wall structures. Optimum parameters of a tuned mass damper for seismically excited structures are determined using several metaheuristic algorithms such as the ant colony optimization, harmony search algorithm, flower pollination algorithm, and bat algorithm [13][14][15][16].…”

An improved Jaya optimization algorithm with Lévy flight

“…The choice of Jaya for this study is motivated by its extreme algorithmic simplicity, coupled with a good optimization performance, which allows us to focus on the effect of Lévy flight without the need to perform an ablation study to dissect the algorithm in all its components. A preliminary investigation of this kind has been recently conducted in (Bekdaş, 2019), although that study focused on the application of various hybrid variants of Lévy flight-based Jaya to a structural design problem, rather than a thorough algorithmic analysis, that is the purpose of the present work. Furthermore, in (Bekdaş, 2019) the details of the Lévy flight model are not discussed, nor the effect of the parametrization on the algorithmic performance.…”

“…A preliminary investigation of this kind has been recently conducted in (Bekdaş, 2019), although that study focused on the application of various hybrid variants of Lévy flight-based Jaya to a structural design problem, rather than a thorough algorithmic analysis, that is the purpose of the present work. Furthermore, in (Bekdaş, 2019) the details of the Lévy flight model are not discussed, nor the effect of the parametrization on the algorithmic performance. To cover this gap, here we study the effect of applying Lévy flight to Jaya thoroughly; also, we discuss the details of the Lévy flight model, and the effect of the β parameter used in the model.…”