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In this paper, controlling the location of the tip of an L-shape beam under gravity field is investigated. The beam is covered with piezoelectric patches. The gravity filed moves the tip of beam downward and the actuators with induced voltage move the tip to the previous location. to optimize the best location and voltages for actuators, the particle swarm optimization algorithm code is developed. The results show that the best position for the most effective actuators is located at the corner of the beam. Also with considering the best location for patches, with lower induced voltage, the location of the tip of beam cab controlled. Also, the results show that with the optimum location of actuators and appropriate voltage lead to using minimum energy with the desired shape in the beam. The results are compared with those reported in previous work.

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During the past two decades, some industries have been moving towards project-centered systems in many modern countries. Therefore, managing simultaneous projects with considering the limitations in resources, equipment and manpower is very crucial. In the real world, project-based organizations are always facing with two main important features. First, the construction projects are decentralized and their distances are long, and second, there are several construction projects undertaken at different time periods. Therefore, appropriate selection of projects with regard to the capabilities of the organization may lead with increasing an expected profitability. This paper investigates the multi-period decentralized multi construction-project and scheduling problem subject to resource constraints, optimal resource pool location, deterioration and batch ordering of nonrenewable resources altogether, for the first time in the literature. In order to describe the problem under consideration in this paper and obtaining the optimal solutions, a mixed integer linear programming model is developed. Finally, the impact of decision integration on the profit profile of an organization is comprehensively investigated by solving numerical examples and through developing some heuristic methods.

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Structural optimization of offshore wind turbine structures has become an important issue in the past years due to the noticeable developments in offshore wind industry. However, considering the offshore wind turbines’ size and environment, this task is outstandingly difficult. To overcome this barrier, in this paper, a metaheuristic algorithm called Enhanced Colliding Bodies Optimization (ECBO) is utilized to investigate the optimal design of jacket supporting structures for offshore wind turbines when a number of structural constraints, including a frequency constraint, are considered. The algorithm is validated using a design example. The OC4 reference jacket, which has been widely referenced in offshore wind industry, is the considered design example in this paper. The whole steps of this research, including loading, analysis, design, and optimization of the structure, are coded in MATLAB. Both Ultimate Limit States (ULS) and frequency constraints are considered as design constraints in this paper. Huge weight reduction is observed during this optimization problem, indicating the efficiency of the ECBO algorithm and its application in the optimization of offshore wind turbine structures.

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This paper presents a practical methodology for optimization of concentrically braced steel frames subjected to forward directivity near-fault ground motions, based on the concept of uniform deformation theory. This is performed by gradually shifting inefficient material from strong parts of the structure to the weak areas until a state of uniform deformation is achieved. In this regard, to overcome the complexity of the ordinary steel concentrically braced frames a simplified analytical model for seismic response prediction of concentrically braced frames is utulized. In this approach, a multistory frame is reduced to an equivalent shear-building model by performing a pushover analysis. A conventional shear-building model has been modified by introducing supplementary springs to account for flexural displacements in addition to shear displacements. It is shown that modified shear-building models provide a better estimation of the nonlinear dynamic response of real framed structures compared to nonlinear static procedures. Finally, the reliability of the proposed methodology has been verified by conducting nonlinear dynamic analysis on 5, 10 and 15 story frames subjected to 20 forward directivity pulse type near-fault ground motions.

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This paper proposes a modified sine cosine algorithm (MSCA) for discrete sizing optimization of truss structures. The original sine cosine algorithm (SCA) is a population-based metaheuristic that fluctuates the search agents about the best solution based on sine and cosine functions. The efficiency of the original SCA in solving standard optimization problems of well-known mathematical functions has been demonstrated in literature. However, its performance in tackling the discrete optimization problems of truss structures is not competitive compared with the existing metaheuristic algorithms. In the framework of the proposed MSCA, a number of worst solutions of the current population is replaced by some variants of the global best solution found so far. Moreover, an efficient mutation operator is added to the algorithm that reduces the probability of getting stuck in local optima. The efficiency of the proposed MSCA is illustrated through multiple benchmark optimization problems of truss structures.

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Water distribution networks are one of the important and costly infrastructures of cities and many meta-heuristic algorithms in standard or hybrid forms were used for optimizing water distribution networks. These algorithms require a large amount of computational cost. Therefore, the converging speed of algorithms toward the optimization goal is as important as the goal itself. In this paper, a new method is developed by linking the charged system search algorithm and firefly algorithm for optimizing water distribution networks. For evaluating the proposed method, some popular benchmark examples are considered. Simulation results demonstrate the efficiency of the proposed algorithm compared to others.

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Existing project selection models do not consider the complexity of projects as a selection criterion, while their complexity may prolong the project duration and even result in its failure. In addition, existing models cannot formulate the aggregate complexity of the selected projects. The aggregated complexity is not always equal to summation of complexity of projects because of possible synergies or conflicts between them may increase or decrease the total complexity. In this paper, a model is proposed for measuring the aggregate complexity in the selection of project portfolios. A case study is presented to show the usefulness of the model and its applicability in practice. Moreover, several large-sized numerical examples have been tested showing the capability of the model to solve such problems in logical computational time.

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The open vehicle routing problem (OVRP) is a variance of the vehicle routing problem (VRP) that has a unique character which is its open path form. This means that the vehicles are not required to return to the depot after completing service. Because this problem belongs to the NP-hard problems, many metaheuristic approaches like the ant colony optimization (ACO) have been used to solve OVRP in recent years. The versions of ACO have some shortcomings like its slow computing speed and local-convergence. Therefore, in this paper, we present an efficient hybrid elite ant system called EHEAS in which a new state transition rule, tabu search as an effective local search algorithm and a new pheromone updating rule are used for more improving solutions. These modifications avoid the premature convergence and make better solutions. Computational results on sixteen standard benchmark problem instances show that the proposed algorithm finds closely the best known solutions for most of the instances in which ten best known solutions are also found. In addition, EHEAS is comparable in terms of solution quality to the best performing published metaheuristics.

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Production planning and inventory control efforts are known as the driving engines of manufacturing systems. The manufacturers, competing to survive in these days’ competitive business environment, aim to satisfy customers’ needs. This requires a precise production plan throughout the supply chain. These days, because of the increasing costs of production and distribution, especially in the cement industry, and given the importance of this industry, investors seek to reduce the production costs as much as possible, to achieve a competitive advantage. In cement industry, main focuses are converging on the alternative fuels developments, optimization of furnace fuel consumptions and sustainable and green production considerations. In this study, a mathematical model is developed to investigate the cement production plan. The objective function is to minimize the total costs of a real case of cement industry. The proposed model is applied on a case of real world application at the West Azerbaijan’s Urmia Cement Company. Sensitivity analyses are carried out on the findings of the model. The proposed model has proven to be cost efficient.

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One of the most important problems discussed recently in structural engineering is the structural reliability analysis considering uncertainties. To have an efficient optimization process for designing a safe structure, firstly it is required to study the effects of uncertainties on the seismic performance of structure and then incorporate these effects on the optimization process. In this study, a new procedure developed for incorporating two important sources of uncertainties in design optimization process of steel moment resisting frames, is proposed. The first source is related to the connection parameter uncertainties and the second one to seismic demand uncertainty. Additionally Mont Carlo (MC) simulation and a variance reduction technique (VRT) are utilized to deal with uncertainties and to reduce the corresponding computational cost. In the proposed procedure two design objectives are considered, which are structural weight and collapse prevention reliability index for a moment resisting frame in such a way that leads to a set of optimum designs with minimum weight and less possible amounts of sensitivity to connection parameters uncertainties and spectral acceleration uncertainty as seismic demand variation. Additionally, in this procedure the reliability index is computed considering all FEMA-356 performance acceptance criteria, the approach that has never been investigated in other studies. The efficiency of this approach is illustrated by exhibiting a set of optimum designs, in the form of both objective values and investigating nonlinear behavior of optimum designs compared with non-optimum designs. This procedure is introduced in this paper with emphasize on the collapse limit state and applying pushover analysis for studying the nonlinear behavior of structural elements.

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Composite RCS building frames integrate reinforced concrete columns with structural steel beams to provide an efficient solution for the design and construction of earthquake-resisting structures. In this paper, an optimization framework is developed for performance-based seismic design of planar RCS moment resisting frames. The objective functions are defined as minimizing the construction cost and the seismic damage. The design variables are obtained in a two-stage design optimization procedure; the elastic design in which column cross-section dimensions are determined and the inelastic design in which beam cross-sections and column reinforcements are obtained. Two design examples are presented to demonstrate the applicability and efficiency of the proposed method. Based on the obtained results, it is concluded that the proposed design optimization procedure is a viable approach in producing cost effective seismic designs of composite RCS frames, with reliable seismic performance and reduced damage potential in the event of a severe earthquake ground motion.

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In this paper, the bi-directional evolutionary structural optimization (BESO) method is used to find optimal layouts of 3D prestressed concrete beams. Considering the element sensitivity number as the design variable, the mathematical formulation of topology optimization is developed based on the ABAQUS finite element software package. The surface-to-surface contact with a small sliding between concrete and prestressing steels is assumed to accurately model the prestressing effects. The concrete constitutive model used is the concrete damaged plasticity (CDP) model in ABAQUS. The integration of the optimization algorithm and finite element analysis (FEA) tools is done by using the ABAQUS scripting interface. A pretensioned prestressed simply supported beam is modeled to show capabilities of the proposed method in finding optimal topologies of prestressed concrete beams. Many issues relating to topology optimization of prestressed concrete beams such as the effects of prestressing stress, geometrical discontinuities and height constraints on optimal designs and strut-and-tie models (STMs) are studied in the example. The results show that the proposed method can efficiently be used for layout optimization of prestressed concrete beams.

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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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Nowadays, steel shear walls are used as efficient lateral-load-resistant systems due to their high lateral stiffness and carrying capacity. In this paper, the effect of substituting a shape memory alloy (SMA) material is investigated instead of using conventional steel in the shear wall. A numerical study is conducted using finite element method (FEM) by OpenSees software. For this purpose, at first, to verify the numerical simulation, the results of the experimental data are compared with those obtained from the numerical phase. Finally, the behavior of a one-bay three-story steel frame equipped with shear walls made of conventional steel, shape memory alloy and a combination of these two materials are studied when the structure is subjected to cyclic and seismic loadings. Results indicate that the use of shape memory alloy increases the maximum deformation, the yield displacement, and also the loading capacity of the structure. Also, it decreases the residual deformation of the structure and its initial stiffness. In general, using composite materials of conventional steel and shape memory alloy can reduce the maximum value of compression axial load of the column and, as a result, increase maximum rotation at the connections. In addition, the minimum and maximum values of base shear occurred in the model with 50% and 25% of Ni-Ti SMA material, respectively.

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The present study addresses optimal design of reinforced concrete (RC) columns based on equivalent equations considering deformability regulations of ACI318-14 under axial force and uniaxial bending moment. This study contrary to common approaches working with trial and error approach in design, at first presents an exact solution for intensity of longitudinal reinforcement in column section by solving equivalent equation. Then, longitudinal and transverse reinforcement details are assessed regarding the previous step results and where achieving the lowest steel consumption design in the column is selected as the optimum. In addition to optimizing column cross-section dimension by implementing single-variable optimization methods, the effect of axial force, bending moment and concrete compressive strength variations on the column cross-section dimension, intensity of longitudinal reinforcement, construction costs and total weight of consumption steel have been investigated. The investigation on the validity of the proposed method was assessed and signified through comparison with the existed work in the literature. Finding an exact solution considering all regulations and constraints is the advantage of this method in determining optimized RC column.

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Active tuned mass damper (ATMD) systems have attracted the considerable attention of researchers for protecting buildings subjected to earthquake loading. This paper presentes the development of an optimal sliding mode control (OSMC) system for a building equipped with ATMD. In the OSMC technique, a linear sliding surface is used with the slope of this surface designed such that a given (or desired) cost function is minimized. The design is obtained by transforming the system into the regular form. In the regular form, the system is divided into two subsystems inclding: a control term explicitly appears, and other control terms do not appear. In order to demonstrate the capability of the OSMC system, an 11–story realistic building with a TMD installed on the top story of the structure is considered. For achieving this purpose, four well–known earthquake records are selected to evaluate the performance of the OSMC system. Results show that the OSMC technique performs better than other control techniques in the reduction of seismic responses of the structure.

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This paper aims to obtain the optimal distance between the adjacent structures using Particle Swarm Optimization (PSO) algorithm considering structure-soil-structure systems; The optimization algorithm has been prepared in MATLAB software and connected into OpenSees software (where the structure-soil-structure system has been analyzed by the direct approach). To this end, a series of adjacent structures with various slenderness have been modeled on the three soil types according to Iranian seismic code (Standard No. 2800) using the direct method. Then they have been analyzed under six earthquake excitations with different risk levels (low, moderate, and high).
The results are compared with the proposed values of separation gap between adjacent structures in the Iranian seismic code (Standard No. 2800). Results show that since structures with the same height constructed on a stiff soil will move in the same phase, there is no need to put distance between them. Although, the structures with the height more than 6-story frames where are located on a soft soil are needed to be separated. Additionally, the results show more separation gap between two adjacent structures when the risk level of earthquake is high. In general, the values which are presented in Standard No. 2800 are not suitable for low /moderate-rise structures specially when they are subjected to a high-risk level earthquake and are located on a soft soil and this separation gap should be increased about 10 to 90 percentage depend on the conditions but these values are appropriate for the adjacent structures with same height where are subjected to a low-risk level earthquakes built on soft soil.

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Dampers can reduce structural response under dynamic loads. Since dampers are costly, the design of structures equipped with dampers should make their application economically justifiable. Among the effective cost reduction factors is optimal damper placement. Hence, this study intended to find the optimal viscous damper placement using efficient optimization methods. Taking into account the nonlinear behavior of structure, this optimal distribution can be determined through meeting story-wise damping requirements such that the structure provides the minimum dynamic response and becomes economically justified. To compare the effect of different damper placement layouts on structural response and determine the objective function of optimization, the ratio of peak structural displacement to yield displacement was used as the damage index and objective function of optimization. Colliding Bodies' Optimization (CBO) algorithm was used for optimal damper placement. In this study, the 3- and 4-story concrete frames with different damper placement conditions were studied. Results confirmed the efficiency of the proposed method and algorithm in optimal viscous damper placement in each story. It was also discovered that the application of dampers on higher stories partially uniforms height-wise damage distribution and works towards the design goals.

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In structural design, either the experience of designer is used or a uniform grouping is usually utilized to group the elements. This type of grouping affects the fundamental cost of the buildings, including the cost of concrete, steel and formwork, as well as secondary costs such as laboratory, checking, fabrication and etc. However, the secondary costs are not usually considered in the cost function. Strategies can also be used to automate the grouping of members in structural design. In this strategy beams and columns are automatically grouped into a limited number of groups to achieve the lowest cost. In this study, enhanced colliding bodies optimization algorithm is used to automatically group the beams and columns of the reinforced concrete structures and also to optimize their cost. The proposed procedure applied to three reinforced concrete frames with four, eight and twelve stories and the influence of automatic grouping of the members in optimal cost is investigated. Using this method, the beams and columns are automatically grouped and the results show that the optimal cost obtained from the automatic grouping is less than the manual grouping of the members.

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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.