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An efficient methodology is proposed to find optimal shape of arch dams on the basis of constrained natural frequencies. The optimization is carried out by virtual sub population (VSP) evolutionary algorithm employing real values of design variables. In order to reduce the computational cost of the optimization process, the arch dam natural frequencies are predicted by properly trained back propagation (BP) and wavelet back propagation (WBP) neural networks. The WBP network provides better generalization compared with the standard BP network. The numerical results demonstrate the computational merits of the proposed methodology for optimum design of arch dams.

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Optimal design of large-scale structures is a rather difficult task and the computational efficiency of the currently available methods needs to be improved. In view of this, the paper presents a modified Charged System Search (CSS) algorithm. The new methodology is based on the combination of CSS and Particle Swarm Optimizer. In addition, in order to improve optimization search, the sequence of tasks entailed by the optimization process is changed so that the updating of the design variables can directly be performed after each movement. In this way, the new method acts as a single-agent algorithm while preserving the positive characteristics of its original multi-agent formulation.

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In this paper, an efficient optimization algorithm is proposed based on Particle Swarm Optimization (PSO) and Simulated Annealing (SA) to optimize truss structures. The proposed algorithm utilizes the PSO for finding high fitness regions in the search space and the SA is used to perform further investigation in these regions. This strategy helps to use of information obtained by swarm in an optimal manner and to direct the agents toward the best regions, resulting in possible reduction of the number of particles. To show the computational advantages of the new PSO-SA method, some benchmark numerical examples are studied. The PSO-SA algorithm converges to better or at least the same solutions, while the number of structural analyses is significantly reduced

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Engineering optimization needs easy-to-use and efficient optimization tools that can be employed for practical purposes. In this context, stochastic search techniques have good reputation and wide acceptability as being powerful tools for solving complex engineering optimization problems. However, increased complexity of some metaheuristic algorithms sometimes makes it difficult for engineers to utilize such techniques in their applications. Big- Bang Big-Crunch (BB-BC) algorithm is a simple metaheuristic optimization method emerged from the Big Bang and Big Crunch theories of the universe evolution. The present study is an attempt to evaluate the efficiency of this algorithm in solving engineering optimization problems. The performance of the algorithm is investigated through various benchmark examples that have different features. The obtained results reveal the efficiency and robustness of the BB-BC algorithm in finding promising solutions for engineering optimization problems.

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In the present study, the computational performance of the particle swarm optimization (PSO) harmony search (HS) and firefly algorithm (FA), as popular metaheuristics, is investigated for size and shape optimization of truss structures. The PSO was inspired by the social behavior of organisms such as bird flocking. The HS imitates the musical performance process which takes place when a musician searches for a better state of harmony, while the FA was based on the idealized behavior of the flashing characteristics of natural fireflies. These algorithms were inspired from different natural sources and their convergence behavior is focused in this paper. Several benchmark size and shape optimization problems of truss structures are solved using PSO, HS and FA and the results are compared. The numerical results demonstrate the superiority of FA to HS and PSO.

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Tunnel structures are known as expensive infrastructures and determining optimum designs of these structures can play a great role in minimizing their cost. The formulation of optimum design of industrial tunnel sections as an optimization is considered in this paper and then the enhanced charged system search, as a recently developed meta-heuristic approach, has been applied to solve the problem. The results and comparisons based on numerical examples show the efficiency of the optimization algorithm.

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The main object of this research is to optimize an end-filled castellated beam. In order to support high shear forces close to the connections, sometimes it becomes necessary to fill certain holes in web opening beam. This is done by inserting steel plates and welding from both sides. Optimization of these beams is carried out using three meta-heuristic methods involves CSS, CBO, and CBO-PSO algorithms. To compare the performance of these algorithms, the minimum cost of the beam is taken as the design objective function. Also, in this study, two common types of laterally supported castellated beams are considered as design problems: beams with hexagonal openings and beams with circular openings. A number of design examples are considered to solve in this case. Comparison of the optimal solution of these methods demonstrates that the hexagonal beams have less cost than cellular beams. It is observed that optimization results obtained by the CBO-PSO for more design examples have less cost in comparison to the results of the other methods.

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This paper utilizes recent optimization algorithm called Ant Lion Optimizer (ALO) for optimal design of skeletal structures. The ALO is based on the hunting mechanism of Antlions in nature. The random walk of ants, building traps, entrapment of ants in traps, catching preys, and re-building traps are main steps for this algorithm. The new algorithm is examined by designing three truss and frame design optimization problems and its performance is further compared with various classical and advanced algorithms.

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For optimization of real-world arch dams, it is unavoidable to consider two or more conflicting objectives. This paper employs two multi-objective differential evolution algorithms (MoDE) in combination of a parallel working MATLAB-APDL code to obtain a set of Pareto solutions for optimal shape of arch dams. Full dam-reservoir interaction subjected to seismic loading is considered. A benchmark arch dam is then examined as the numerical example. The numerical results are compared to show the performance of the MoDE methods.

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In this study, constant-ductility optimization algorithm under a family of earthquake ground motions is utilized to achieve uniform damage distribution over the height of steel moment resisting frames (SMRFs). SMRF structures with stiffness-degrading hysteric behavior are modeled as single-bay generic frame in which the plastic hinge is confined only at the beam ends and the bottom of the first story columns. Several SMRFs having different fundamental periods and number of stories are optimized such that a uniform story damage (ductility demand) is obtained under a given earthquake ground motion. Then, the optimum lateral load pattern derived from the optimization process is compared with that of the design load pattern proposed by the latest version of the Iranian code of practice, Standard No. 2800 to evaluate the adequacy of the seismic code design pattern. Results of this study indicate that, generally, the average story shear strength profiles corresponding to the optimum seismic design are significantly different from those of the Standard No. 2800 story shear strength pattern. In fact, the height-wise distribution of story ductility demands resulted from utilizing code-based design lateral load pattern are very non-uniform when compared to the corresponding optimum cases. In addition, a significant dependency is found between the average story shear strength pattern and inelastic behavior of structural elements.

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In the present study, ten steel-moment resisting frames (SMRFs) having different numbers of stories ranging from 3 to 20 stories and fundamental periods of vibration ranging from 0.3 to 3.0 second were optimized subjected to a set of earthquake ground motions using the concept of uniform damage distribution along the height of the structures. Based on the step-by-step optimization algorithm developed for uniform damage distribution, ductility-dependent strength reduction factor spectra were computed subjected to a given far-fault earthquake ground motion. Then, the mean ductility reduction factors subjected to 20 strong ground motions were computed and compared with those designed based on load pattern of ASCE-7-16 (similar to standard No. 2800) code provision. Results obtained from parametric studies indicate that, except in short-period structures, for moderate and high levels of inelastic demand the structures designed based on optimum load pattern with uniform damage distribution along the height require larger seismic design base shear strength when compared to the frames designed based on the code provisions, which is more pronounced for long-period structures i.e., the structural system becomes more flexible. This phenomenon can be associated to the P-delta effect tending to increase the story drift ratios of flexible structures, especially at the bottom stories. For practical purpose, a simplified expression which is a function of fundamental period and ductility demand to estimate ductility-dependent strength reduction factors of designed SMRFs according to code-based lateral load pattern is proposed.

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Hybrid control system composed of a base isolation system and a magneto-rheological damper so-called smart base isolation is one of effective semi-active control system in controlling the seismic response of structures. In this paper, a design method is proposed for designing the smart base isolation system in order to achieve an effective performance under multiple earthquakes. The base mass, the base stiffness and the weighting parameter of H₂/linear quadratic Gaussian control algorithm, which is used to determine the desired control force, have been considered as the design variables and different earthquake records have been considered as design earthquakes. First, the optimum values of these variables under each of the considered earthquakes have been determined by using the genetic algorithm and then, an optimum control system has been designed with multiple earthquakes-based design approach. The defined design objective is minimizing the peak base drift while the peak inter-story drift has been constrained. For numerical simulation, smart base isolation system is designed for controlling a four-story shear frame. The results show that when the control system designed for a specific earthquake is subjected to another earthquake, difference between the performance of this control system and the optimal case under that earthquake is considerable. Hence, the specific earthquake-based design approach is an inappropriate design procedure for smart base isolation. Also, it has been found that control system designed based on multiple earthquakes-based design approach shows effective performance in controlling the response of structure under a wide range of earthquakes.

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The optimal design of dome structures is a challenging task and therefore the computational performance of the currently available techniques needs improvement. This paper presents a combined algorithm, that is supported by the mixture of Charged System Search (CSS) and Teaching-Learning-based optimization (TLBO). Since the CSS algorithm features a strong exploration and may explore all unknown locations within the search space, it is an appropriate complement to enhance the optimization process by solving the weaknesses with using another optimization algorithm’s strong points. To enhance the exploitation ability of this algorithm, by adding two parts of Teachers phase and Student phase of TLBO algorithm to CSS, a method is obtained that is more efficient and faster than standard versions of these algorithms. In this paper, standard optimization methods and new hybrid method are tested on three kinds of dome structures, and the results show that the new algorithm is more efficient in comparison to their standard versions.

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In present study, the effects of optimization on seismic energy spectra including input energy, damping energy and yielding hysteretic energy are parametrically discussed. To this end, 12 generic steel moment-resisting frames having fundamental periods ranging from 0.3 to 3s are optimized by using uniform damage and deformation approaches subjected to a series of 40 non-pule strong ground motions. In order to obtain the optimum distribution of structural properties, an iterative optimization procedure has been adopted. In this approach, the structural properties are modified so that inefficient material is gradually shifted from strong to weak areas of a structure. This process is continued until a state of uniform damage is achieved. Then, the maximum energy demand parameters are computed for different structures designed by optimum load pattern as well as code-based pattern, and the mean energy spectra, energy-based reduction factor and the dispersion of the results are compared and discussed. Results indicate that optimum seismic load pattern can significantly affect the energy demands spectra especially in inelastic range of response. In addition, using energy-based reduction factors of optimum structures in short-period and long-period regions will result in respectively overestimation and underestimation of the required input energy demands for code-based structures, reflecting the difference dose exists in reality between the conventional forced-based methodology and energy-based seismic design approach that can more realistically incorporate the frequency content and duration of earthquake ground motions.