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Öğe Investigation of optimal designs for concrete cantilever retaining walls in different soils(2020) Uray, Esra; Çarbaş, Serdar; Erkan, İbrahim Hakkı; Olgun, MuratIn this paper, the investigation of the optimum designs for two types of concrete can-tilever retaining walls was conductedutilizing the artificial bee colony algorithm. Sta-bility conditions like safety factors of sliding, overturningand bearing capacity and some geometric instancesdue to inherent of the wall were considered as the design constraints. The effect of the existence of the key in wall design on the objective func-tion was probed for changeableproperties of foundation and backfill soils. In optimi-zation analysis, the concrete of the wall, which directly affectsparameters such as carbon dioxide emission and the cost,was considered as the objective function and analyzes were performed according to different discrete design variables. The opti-mum concrete cantilever retaining wall designs satisfying constraints of stability conditions and geometric instanceswere obtained for different soil cases. Optimum designs of concrete cantilever retaining wall with the key were attained in some soil cases which were not foundthe feasible optimum solution of the concrete cantilever retaining wall. Results illustratethat the artificial bee colony algorithm was a favor-ablemetaheuristic optimization method togainoptimum designs of concrete canti-lever retaining wall.Öğe Investigation of parametric effect in optimum retaining wall design using harmony search algorithm(Springer Science and Business Media Deutschland GmbH, 2022) Uray, Esra; Çarbaş, Serdar; Olgun, MuratThis study focuses on the investigation of the parametric effect of the harmony search algorithm on design variables for optimum cantilever retaining wall design. Variance analyses have been performed for the detection of design parameters which are taken as discrete variables in the optimization process and percentages of the parameter effect have been calculated, as well. Optimum results obtained by the harmony search algorithm have been examined according to the parameter effect of design variables statistically determined via the Taguchi method. Eventually, the attained results have shown that changing the value of the effective design parameter in the design positively contributes to the optimization process. In addition, it has been observed that developing a new solution for the design parameter which has little effect on the design is not significant in converging to the optimum solution.Öğe Metaheuristics-based pre-design guide for cantilever retaining walls(Turkish Chamber of Civil Engineers, 2021) Uray, Esra; Tan, Özcan; Çarbaş, Serdar; Erkan, İbrahim HakkıA pre-design guide for cantilever retaining walls and a detail parametric study of such walls is presented here. Mathematical models based on statistical methods were improved for calculating safety factors of sliding, overturning, and slope stability of those walls. The harmony search algorithm (HSA)-a metaheuristic method-was employed to realize reasonable results of the pre-design guide from all distinct cases. Through the design algorithm, the optimal design was determined for varied soil types differently from suggestions of design codes. Thus, an optimal pre-design guide for safe and economic wall design was realized in a shorter time compared to the conventional method.Öğe Modeling Civil Engineering Problems via Hybrid Versions of Machine Learning and Metaheuristic Optimization Algorithms(Springer Science and Business Media Deutschland GmbH, 2023) Demir, Vahdettin; Uray, Esra; Carbas, SerdarThe aim of this study is to develop hybrid solution models by integrating metaheuristic optimization algorithms and machine learning technique. These hybrid models are utilized to estimate bearing capacity of pile groups and lake levels, which are common challenges to calculate in the geotechnical and hydrology designs of civil engineering. To achieve this, Lake Beyşehir lake-water level observations and various pile group designs are used as a dataset, which is divided into two parts; 75% for training and 25% for testing. By employing improved hybrid models that combine metaheuristic algorithms such as harmony search, artificial bee colony, and particle swarm optimization with a machine learning technique called least squares support vector regression (LSSVR), optimal values of kernel parameters are obtained reliably and robustly. The results suggest that these hybrid models can be successfully applied to complex real-world problems, as evidenced by nine evaluation metrics, including mean absolute error (MAE), root mean squared error (RMSE), and determination coefficient (R2), which showed satisfactory and reasonable performance. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.Öğe Parameters optimization of taguchi method ıntegrated hybrid harmony search algorithm for engineering design problems(MDPI, 2022) Uray, Esra; Çarbaş, Serdar; Geem, Zong Woo; Kim, SanghunPerformance of convergence to the optimum value is not completely a known process due to characteristics of the considered design problem and floating values of optimization algorithm control parameters. However, increasing robustness and effectiveness of an optimization algorithm may be possible statistically by estimating proper algorithm parameters values. Not only the algorithm which utilizes these estimated-proper algorithm parameter values may enable to find the best fitness in a shorter time, but also it may supply the optimum searching process with a pragmatical manner. This study focuses on the statistical investigation of the optimum values for the control parameters of the harmony search algorithm and their effects on the best solution. For this purpose, the Taguchi method integrated hybrid harmony search algorithm has been presented as an alternative method for optimization analyses instead of sensitivity analyses which are generally used for the investigation of the proper algorithm parameters. The harmony memory size, the harmony memory considering rate, the pitch adjustment rate, the maximum iteration number, and the independent run number of entire iterations have been debated as the algorithm control parameters of the harmony search algorithm. To observe the effects of design problem characteristics on control parameters, the new hybrid method has been applied to different engineering optimization problems including several engineering-optimization examples and a real-size engineering optimization design. End of extensive optimization and statistical analyses to achieve optimum values of control parameters providing rapid convergence to optimum fitness value and handling constraints have been estimated with reasonable relative errors. Employing the Taguchi method integrated hybrid harmony search algorithm in parameter optimization has been demonstrated as it is a reliable and efficient manner to obtain the optimum results with fewer numbers of run and iteration.Öğe Parametric investigation for discrete optimal design of a cantilever retaining wall(2019) Uray, Esra; Çarbaş, Serdar; Erkan, İbrahim Hakkı; Tan, ÖzcanIn this paper, discrete design optimization of a cantilever retaining wall has been sub-mitted associated with a detailed parametric study of the wall. In optimal design, the minimum wall weight is treated as the objective function. Through design algorithm, the optimal design variables (base width, toe width, thickness of base slab and angle of front face) yielded minimum structural weight of the wall and satisfied stability conditions have been determined for different soil parameter values. At the end, a detail parametric study searching the effect of change of soil parameters on the re-taining wall design has been conducted with 120 optimized wall designs for different values; eight values of the angle of internal friction, three values of the unit volume weight and five values of wall heights. The obtained results from optimization anal-yses indicate that change of the angle of internal friction more effective than change of the unit volume weight on the optimal wall weight. Economic wall design with op-timization analysis is achieved in a shorter time than the traditional method.
