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Due to the complex structural issues and increasing number of design variables, a rather fast optimization algorithm to lead to a global swift convergence history without multiple attempts may be of major concern. Genetic Algorithm (GA) includes random numerical technique that is inspired by nature and is used to solve optimization problems. In this study, a novel GA method based on self-adaptive operators is presented. Results show that this proposed method is faster than many other defined GA-based conventional algorithms. To investigate the efficiency of the proposed method, several famous optimization truss problems with semi-discrete variables are studied. The results reflect the good performance of the algorithm where relatively a less number of analyses is required for the global optimum solution.

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Semi-active base isolation system has been proposed mainly to mitigate the base drift of isolated structures while in most cases, its application causes the maximum acceleration of superstructure to be increased. In this paper, designing optimal semi-active base isolation system composed of linear base isolation system with low damping and magneto-rheological (MR) damper has been studied for controlling superstructure acceleration and base drift separately and simultaneously. A multi-objective optimization problem has been defined for optimal design of semi-active base isolation system which considers a linear combination of maximum acceleration and base drift as objective function where Genetic algorithm (GA) has been used to solve the optimization problem. H₂/Linear Quadratic Gaussian (LQG) and clipped-optimal control algorithms have been used to determine the desired control force and the voltage of MR damper in each time step. For numerical simulation, a four-story base isolated shear frame has been considered and for different values of weighting parameter in objective function, optimal semi-active base isolation system has been designed under various design earthquakes. The results show that by using base isolation system and supplemental MR damper, the superstructure acceleration and base drift can be suppressed significantly. Also, it has been concluded that by selecting proper values for maximum acceleration and base drift related weighting parameters in objective function, it is possible to mitigate the maximum acceleration and base drift simultaneously. Furthermore, semi-active control system has worked successfully under testing earthquakes regarding design criteria.

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The objective of this work is to predict the temperature of the different types of walls which are Ferro cement wall, reinforced cement concrete (RCC) wall and two types of cavity walls (combined RCC with Ferrocement and combined two Ferro cement walls) with the help of mathematical modeling. The property of low thermal transmission of small air gap between the constituents of combine materials has been utilized to obtain energy efficient wall section. Ferro cement is a highly versatile form of reinforced concrete made up of wire mesh, sand, water, and cement, which possesses unique qualities of strength and serviceability. The significant intention of the proposed technique is to frame a mathematical modeling with the aid of optimization techniques. Mathematical modeling is done by minimizing the cost and time consumed in the case of extension of the existing work. Mathematical modeling is utilized to predict the temperature of the different wall such as RCC wall, Ferro cement, combined RCC with Ferro cement and combined Ferro cement wall. The different optimization algorithms such as Social Spider Optimization (SSO), Genetic Algorithm (GA) and Group Search Optimization (GSO) are utilized to find the optimal weights α and β of the mathematical modeling. All optimum results demonstrate that the attained error values between the output of the experimental values and the predicted values are closely equal to zero with the SSO model. The results of the proposed work are compared with the existing methods and the minimum errors with SSO algorithm for the case of two combined RCC wall was found to be less than 2%.

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Digging of geotechnical boreholes and soil resistance tests are time-consuming and expensive activities. Therefore selection of optimum number and suitable location of boreholes can reduce cost of their drilling and soil resistance tests. In this research, a model which is consisting of geo statistics model as an estimator and an optimized model is selected. The kriging calculates the variance of the estimation error of different combinations from available geotechnical boreholes. In each combination, n is number of considered boreholes and N is number of available boreholes (N>n). At the end, the best combination is selected by genetic algorithm (the error variance of this combination is minimum). Also the Kean Shahr of Ahvaz city (in Khuzestan province, Iran) is selected as case study in this research. Location of selected boreholes is in points that soil resistance of these points represents mean soil resistance of total region. Optimum number of boreholes is 15. Also results show that location of selected boreholes depends to soil resistance and diameter and length of applied piles are not important for this purpose.

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The constitutive relationships presented for concrete modeling are often associated with unknown material constants. These constants are in fact the connectors of mathematical models to experimental results. Experimental determination of these constants is always associated with some difficulties. Their values are usually determined through trial and error procedure, with regard to experimental results. In this study, in order to determine the material constants of an elastic-damage-plastic model proposed for concrete, the results of 44 uniaxial compression and tension experiments collected from literature were used. These constants were determined by investigating the consistency of experimental and modeling results using a genetic algorithm optimization tool for all the samples; then, the precision of resulted constants were investigated by simulating cyclic and biaxial loading experiments. The simulation results were compared to those of the corresponding experimental data. The results observed in comparisons indicated the accuracy of obtained material constants in concrete modeling.

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Structural reliability theory allows structural engineers to take the random nature of structural parameters into account in the analysis and design of structures. The aim of this research is to develop a logical framework for system reliability analysis of truss structures and simultaneous size and geometry optimization of truss structures subjected to structural system reliability constraint. The framework is in the form of a computer program called RBO-S>S. The objective of the optimization is to minimize the total weight of the truss structures against the aforementioned constraint. System reliability analysis of truss structures is performed through branch-and-bound method. Also, optimization is carried out by genetic algorithm. The research results show that system reliability analysis of truss structures can be performed with sufficient accurately using the RBO-S>S program. In addition, it can be used for optimal design of truss structures. Solutions are suggested to reduce the time required for reliability analysis of truss structures and to increase the precision of their reliability analysis.

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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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In this paper, a procedure has been presented to develop fragility curves of structures equipped with optimal variable damping or stiffness semi-active tuned mass dampers (SATMDs). To determine proper variable damping or stiffness of semi-active devices in each time step, instantaneous optimal control algorithm with clipped control concept has been used. Optimal SATMDs have been designed based on minimization of maximum inter-story drift of nonlinear structure which genetic algorithm(GA) has been used to solve the optimization problem. For numerical analysis, a nonlinear eight-story shear building with bilinear hysteresis material behavior has been used. Fragility curves for the structure equipped with optimal variable damping and stiffness SATMDs have been developed for different performance levels and compared with that of uncontrolled structure as well as structure controlled using passive TMD. Numerical analysis has shown that for most range of intensity measure optimal SATMDs have been effective in enhancement of the seismic fragility of the nonlinear structures which the improvement has been more than passive TMDs. Also, it has been found that, although variable stiffness SATMD shows to be more reliable in lower mass ratios, however in higher mass ratios variable stiffness and damping SATMDs performs similarly to improve reliability of the structure.

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Bridges constitute an expensive segment of construction projects; the optimization of their designs will affect their high cost. Segmental precast concrete bridges are one of the most commonly serviced bridges built for mid and long spans. Genetic algorithm is one of the most widely applied meta-heuristic algorithms due to its ability in optimizing cost. Next to providing cost optimization of these bridge types, the effects of each one of the main three selections, crossover and mutation operators are assessed, and the best operator is determined through the Taguchi experimental design. To validate the functionality of this algorithm, a bridge constructed in the city of Isfahan, Iran (completed in 2017) is optimized, a total of 13% reduction in cost and weight of its superstructure is evident. The efficiency of applying the Taguchi method in determining the type of operators of the genetic algorithm is proved.

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In this paper, a design method is proposed for base isolation system under blast loading that this method is based on transforming design problem into an optimization problem. Genetic algorithm has been employed to solve the optimization problem whereas base isolation system properties have been considered as design variables and a linear combination of base drift and inter-story drift has been defined as objective function. A sensitivity analysis has been also conducted to investigate the effect of base isolation system properties on the blast performance of isolated structure. For numerical simulation, base isolation system is designed using the proposed method for controlling the response of an eight-story nonlinear shear-type building frame under blast loading. It has been found from the results that base isolation system is an effective control system under blast loading that its performance is dependent on the base isolation system characteristics especially the base mass. The optimization results also show that base isolation system designed using the proposed method is a well-designed control system for mitigating the blast response of structure and the proposed design method can be considered as an effective design approach under blast loading.

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This paper presents a design process using a course grained parallel genetic algorithm to optimize three-dimensional steel moment frames by considering the axial force and biaxial bending moments interaction in plastic hinge formation. The objective function is to minimize the total weight of the structure subjected to the reliability constraint of the structural system. System reliability analysis is performed through the proposed Modified Latin Hypercube Simulation (M-LHS) Method. For optimization, a 3DSMF-RBO program is written in CSHARP programming language. The reliability analysis results show a large decrease in the number of simulation samples and subsequently a decrease in the execution time of optimization computation. The optimization results indicate that by considering interaction of the axial force and biaxial bending moments in plastic hinge formation rather than the only bending moment, to some extent increases the total weight of the designed structure.

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In this paper, a procedure has been introduced to the multi-objective optimal design of semi-active tuned mass dampers (SATMDs) with variable stiffness for nonlinear structures considering soil-structure interaction under multiple earthquakes. Three bi-objective optimization problems have been defined by considering the mean of maximum inter-story drift as safety criterion of structural components, absolute acceleration as the criterion of occupants’ convenience, and safety of non-structural acceleration sensitive components, as well as SATMD relative displacement as the cost criterion of the control device. The parameters of the weighting matrices of the instantaneous optimal control algorithm and the maximum and minimum level of variable stiffness of the semi-active device have been considered as design variables. An improved version of the non-dominated sorting genetic algorithm (NSGA-II), has been employed to solve the optimization problems and figure out the set of Pareto optimal solutions. SATMDs with different mass ratios have been designed for an eight-story shear type building with bilinear elasto-plastic stiffness model where the soil-structure interaction has been incorporated by Cone model with three degrees of freedom for the soil. Results show the capability and simplicity of the proposed procedure to design SATMDs considering multiple performance criteria. It is observed that this procedure can offer a wide range of optimal solutions throughout the Pareto front which can be chosen by the designer based on desired performance and application of the structure.

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This paper proposes a GA-based reduced search space technique (GA-RSS) for the optimal design of steel moment frames. It tries to reduce the computation time by focusing the search around the boundaries of the constraints, using a ranking-based constraint handling to enhance the efficiency of the algorithm. This attempt to reduce the search space is due to the fact that in most optimization problems the optimal solution lies on or near the boundaries of the feasible region. All the analyses/optimization steps have been implemented in MATLAB and the method has been validated by optimizing three moment-frame benchmark problems. According to the results, the algorithm performs fit and needs relatively fewer analyses than other metaheuristic algorithms to reach a global optimum solution.

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This article presents numerical studies on semi-active seismic response control of structures equipped with Magneto-Rheological (MR) dampers. A multi-layer artificial neural network (ANN) was employed to mitigate the influence of time delay, This ANN was trained using data from the El-Centro earthquake. The inputs of ANN are the seismic responses of the structure in the current step, and the outputs are the MR damper voltages in the current step. The required training data for the neural controller is generated using genetic algorithm (GA). Using the El-Centro earthquake data, GA calculates the optimal damper force at each time step. The optimal voltage is obtained using the inverse model of the Bouc-Wen based on the predicted force and the corresponding velocity of the MR damper. This data is stored and used to train a multi-layer perceptron neural network. The ANN is then employed as a controller in the structure. To evaluate the efficiency of the proposed method, three- story, seven- story and twenty-story structures with a different number of MR dampers were subjected to the Kobe, Northridge, and Hachinohe earthquakes. The maximum reduction in structural drifts in the three-story structure are 13.05%, 39.90%, 15.89%, and 8.21%, for the El-Centro, Hachinohe, Kobe, and Northridge earthquakes, respectively. As the control structure is using a pre-trained neural network, the computation load in the event of an earthquake is extremely low. Additionally, as the ANN is trained on seismic pre-step data to predict the damper's current voltage, the influence of time lag is also minimized.

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This paper introduces a reliability-based multi-objective design method for spatial truss structures. A multi-objective optimization problem has been defined considering three conflicting objective functions including truss weight, nodal deflection, and failure probability of the entire truss structure with design variables of cross sectional area of the truss members. The failure probability of the entire truss system has been determined considering the truss structure as a series system. To this end, the uncertainties of the applied load and the resistance of the truss members have been accounted by generating a set of 50 random numbers. The limitations of members' allowable have been defined as constraints. To explain the methodology, a 25-bar benchmark spatial truss has been considered as the case study structure and has been optimally designed using the game theory concept and genetic algorithm (GA). The results show effectiveness and simplicity of the proposed method which can provide Pareto optimal solution. These optimal solutions can provide both safety and reliability for the truss structure.
 

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This paper presents an efficient wavelet-based genetic algorithm strategy for optimal sensorexciter placement (OSPOEP) in large-scaled structures suitable for time-domain structural identification. For this purpose, a wavelet-based scheme is introduced in order to improve the fitness evaluation of GA-based individuals capable of using adaptive wavelets. A search domain reduction (SDR) strategy is proposed to reduce the wide space of initial unknowns corresponding to enormous degrees-of-freedom in large systems. The proposed reduction strategy is carried out at three stages according to the use of different wavelet functions. Furthermore, a multi-species decimal GA coding system is modified for a competent search around the local optima. In this regards, a local operation of mutation is presented in addition with regeneration and reintroduction operators. It is deduced that, the reliable OSPOEP strategy prior to the time-domain identification will be achieved by those procedures dealing with minimizing the distance of simulated responses for the entire system and condensed system considering the excitation effects. The numerical assessment on the appropriateness and capability of the proposed approach demonstrates the substantially high computational performance and fast convergence of the proposed OSPOEP strategy, especially in large-scaled structural systems. It is concluded that, the robustness of the proposed OSPOEP procedure lies on the precise and fast fitness evaluation at larger sampling rates which resulting in the optimum evaluation of the GA-based exploration and exploitation phases towards the global optimum solution.
 

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The semi-active bracing system locks or unlocks the stand-by braces in an on-off mode utilizing a variable stiffness device (VSD). In this paper, the optimal design of a semi-active bracing mechanism and evaluating its performance in mitigating structural vibration under seismic loading have been studied. The optimal stiffness values of the semi-active braces have been determined by solving two optimization problems including minimizing the maximum acceleration and also minimizing the maximum inter-story drift by imposing a constraint on the maximum acceleration. The genetic algorithm (GA) has been applied to solve the optimization problems. To illustrate the design procedure, an eight-story linear shear frame under earthquake record has been considered and the optimal semi-active braces have been designed. In addition, to assess the performance of optimal bracing system under other records which are different from design record in terms of intensity and frequency content, the structure equipped with optimally designed semi-active braces has been tested under several ground motion records. The results show that the optimal semi-active bracing system has simultaneously reduced different responses of the structure although the acceleration reduction has mainly been less compared to the drift reduction.
 

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Structural topology optimization provides an insight into efficient designing as it seeks optimal distribution of material to minimize the total cost and weight of the structures. This paper presents an optimum design of steel moment frames and connections of structures subjected to serviceability and strength constraints in accordance with AISC-Load and Resistance Factor Design (LRFD). In connection topology optimizations, different beam and column sections and connections and also to optimize two steel moment frames a genetic algorithm was used and their performance was compared. Initially, two common steel moment frames were studied, only for the purpose of minimizing the weight of the structure and the members of structure are considered as design variables. Since the cost of a steel moment frame is not solely related to the weight of the structure, in order to obtain a realistic plan, in the second part of this study, for the other two frames the cost of the connections is also added to the variables. The results indicate that the steel frame optimization by applying real genetic algorithm could be optimal for structural designing. The findings highlighted the prominent performance and lower costs of the steel moment frames when different connections are used.
 

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Genetic algorithm is a robust meta-heuristic algorithm inspired by the theory of natural selection to solve various optimization problems. This study presents a method with the purpose of promoting the exploration and exploitation of genetic algorithm. Improvement in exploration ability is made by adjusting the initial population and adding a group of fixed stations. This modification increases the diversity among the solution population, which enables the algorithm to escape from local optimum and to converge to the global optimum even in fewer generations. On the other hand, to enhance the exploitation ability, increasing the number of selected parents is suggested and a corresponding crossover technique has been presented. In the proposed technique, the number of parents to generate offspring is variable during the process and it could be potentially more than two. The effectiveness of the modifications in the proposed method has been verified by examining several benchmark functions and engineering design problems.