Performance 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.
In this paper, discrete design optimization of a cantilever retaining wall has been submitted 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 retaining 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 analyses 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 optimization analysis is achieved in a shorter time than the traditional method.
A 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.
In this paper, the investigation of the optimum designs for two types of concrete cantilever retaining walls was performed utilizing the artificial bee colony algorithm. Stability conditions like safety factors sliding, overturning and bearing capacity and some geometric instances due 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 function was probed for changeable properties of foundation and backfill soils. In optimization analysis, wall concrete weight which directly affect parameters 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 optimum concrete cantilever retaining wall designs satisfying constraints of stability conditions and geometric instances were obtained for different soil cases. Optimum designs of concrete cantilever retaining wall with the key were attained in some soil cases which were not found the feasible optimum solution of the concrete cantilever retaining wall. Results illustrate that the artificial bee colony algorithm was a favorable metaheuristic optimization method to gain optimum designs of concrete cantilever retaining wall.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.