International Journal of Optimization in Civil Engineering
Volume:6 Issue: 4, Autumn 2016

This paper presents a novel population-based meta-heuristic algorithm inspired by the game of tug of war. Utilizing a sport metaphor the algorithm, denoted as Tug of War Optimization (TWO), considers each candidate solution as a team participating in a series of rope pulling competitions. The teams exert pulling forces on each other based on the quality of the solutions they represent. The competing teams move to their new positions according to Newtonian laws of mechanics. Unlike many other meta-heuristic methods, the algorithm is formulated in such a way that considers the qualities of both of the interacting solutions. TWO is applicable to global optimization of discontinuous, multimodal, non-smooth, and non-convex functions. Viability of the proposed method is examined using some benchmark mathematical functions and engineering design problems. The numerical results indicate the efficiency of the proposed algorithm compared to some other methods available in literature.

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.

Presenting structural damage detection problem as an inverse model-updating approach is one of the well-known methods which can reach to informative features of damages. This paper proposes a model-based method for fault prognosis in engineering structures. A new damage-sensitive cost function is suggested by employing the main concepts of the Modal Assurance Criterion (MAC) on the first several modes’ data. Then, Chaotic Imperialist Competitive Algorithm (CICA), a modified version of the original Imperialist Competitive Algorithm (ICA) which has recently been developed for optimal design of complex trusses, is employed for solving the suggested cost function. Finally, the optimal solution of the problem is reported as damage detection results. The efficiency of the proposed method for damage identification is evaluated by studying three numerical examples of structures. Several single and multiple damage patterns are simulated and different number of modal data are utilized as input data (in noise free and noisy states) for damage detection via suggested method. Moreover, different comparative studies are carried out for evaluating the preference of the suggested method. All the obtained results emphasize the high level of accuracy of the suggested method and introduce it as a viable method for identifying not only damage locations, but also damage severities.

This study investigates the efficacy of optimal semi-active dampers for achieving the best results in seismic response mitigation of adjacent buildings connected to each other by magnetorheological (MR) dampers under earthquakes. One of the challenges in the application of this study is to develop an effective optimal control strategy that can fully utilize the capabilities of the MR dampers. Hence, a SIMULINK block in MATLAB program was developed to compute the desired control forces at each floor level and to the obtain number of dampers. Linear quadratic regulator (LQR) and linear quadratic Gaussian (LQG) controllers are used for obtaining the desired control forces, while the desired voltage is calculated based on clipped voltage law (CVL). The control objective is to minimize both the maximum displacement and acceleration responses of the structure. As a result, MR dampers can provide significant displacement response control that is possible with less voltage for the shorter building.

In this paper, two different data driven models, genetic programming (GP) and multivariate adoptive regression splines (MARS), have been adopted to create the models for prediction of bridge risk score. Input parameters of bridge risks consists of safe risk rating (SRR), functional risk rating (FRR), sustainability risk rating (SUR), environmental risk rating (ERR) and target output. The total dataset contains 66 bridges data in which 70% of dataset is taken as training and the remaining 30% is considered for testing dataset. The accuracy of the models are determined from the coefficient of determination (R2). If the R2 the testing model is close to the R2 value of the training model, that particular model is to be consider as robust model. The modeling mechanisms and performance is quite different for both the methods hence comparative study is carried out. Thus concluded robust models performance based on the R2 value, is checked with mathematical statistical equations. In this study both models were performed, examined and compared the results with mathematical methods successfully. From this work, it is found that both the proposed methods have good capability in predestining the results. Finally, the results reveals that genetic Programming is marginally outperforms over the MARS technique.

The increasing complexity of construction, along with its rapid development, as well as ambiguities and gaps in the legal terms governing constructions, lack of trust in the parties regarding obligations and regulations are the main reasons of disagreements in domestic projects. These disagreements are inevitable even in contracts which are set correctly. Disagreements are costly, time-consuming and inconvenient. They also affect the price and quality of contracts. In most projects using different delivery systems, entities particularly contractors may make claims. Moreover, claims and disagreements are inevitable in Design-Bid projects, particularly in Design-Bid-Build (D-B-B) contracts, which are not commonly used in Iran. The focus of this study is the reasons for claims made in projects delivered by Design-Bid-Build (D-B-B) contracts. This study also observes claims related to consulting engineer of the owner. Accordingly, different criteria and sub-criteria are determined to prioritize by decision-making models.

Stochastic nature of earthquake has raised a challenge for engineers to choose which record for their analyses. Clustering is offered as a solution for such a data mining problem to automatically distinguish between ground motion records based on similarities in the corresponding seismic attributes. The present work formulates an optimization problem to seek for the best clustering measures. In order to solve this problem, the well-known K-means algorithm and colliding bodies optimization are employed. The latter acts like a parameter-less meta-heuristic while the former provides strong intensification. Consequently, a hybrid algorithm is proposed by combining features of both the algorithms to enhance the search and avoid premature convergence. Numerical simulations show competative performance of the proposed method in the treated example of optimal ground motion clustering; regarding global optimization and quality of final solutions.

In this study, optimum combinations of available rainfall gauging stations are selected by a model which is consist of geo statistics model as an estimator and an optimized model. At the first, watershed is approximated to several regular geometric shapes. Then kriging calculates the variance of the estimation error of different combinations from available rainfall gauging stations using inside and outside stations of watershed. In each combination, n is number of considered stations and N is number of available stations (N>n). At the end, the best combination is selected by genetic algorithm (the error variance of this combination is minimum). For optimal set with one sample point (station) estimator model and optimize model select station that locates near to center of watershed. While for two stations case, these models select two stations that l ocate in boundaries face to face. Also for combination n stations of N stations, selected stations have good and proportional distribution in watershed. These results show correctness of research methodology.
In this study, effects of variations of paramet ers of theoretical variogram and number of blocks in block estimation of kriging method are evaluated too. The variance of the estimation error from block estimation with 8*8 blocks has showed the acceptable results.
This research shows a linear relation between variations of error variance and scale of variogram. Optimum combination does not vary with variations of scale of variogram but it varies with variations of range of variogram. Increasing of nugget effect of variogram would raise the variance but does not vary optimum combinations.

Tuned mass dampers (TMDs) are as a efficient control tool in order to reduce undesired vibrations of tall buildings and large–span bridges against lateral loads such as wind and earthquake. Although many researchers has been widely investigated TMD systems due to its simplicity and application, the optimization of parameters and placement of TMD are challenging tasks. Furthermore, ignoring the effects of soil–structure interaction (SSI) may lead to unrealistic desig of structure and its dampers. Hence, the effects of SSI should be considered in the design of TMD. Therefore, the main aim of this study is to optimize parameters of TMD subjected to earthquake and considering the effects of SSI. In this regard, the parameters of TMD including mass, stiffness and damping optimization are considered as the variables of optimization. The maximum absolute displacement and acceleration of structure are also simultaneously selected as objective functions. The multi –objective particle swarm optimization (MOPSO) algorithm is adopted to find the optimal parameters of TMD. In this study, the Lagrangian method is utilized for obtaining the equations of motion for SSI system, and the time domain analysis is implemented based on Newmark method. In order to investigate the effects of SSI in the optimal design of TMD, a 40 storey shear building with a TMD subjected to the El–Centro earthquake is considered. The numerical results show that the SSI effects have the significant influence on the optimum parameters of TMD.

Due to several uncertainties which affect structural responses of Reinforced concrete (RC) frames, it is sensibly required to apply a vulnerability analysis tool such as fragility curve. To construct an analytical fragility curve, the incremental dynamic analysis (IDA) method has been extensively used as an applicable seismic analysis tool. To employ the IDA method for constructing fragility curves of RC frames, it is important to know how many records will be adequate to assess seismic risk analysis properly? Another issue is to know how many IDA steps are required for developing an accurate fitted fragility function? For this purpose, two 3D RC frames called 3STRCF and 5STRCF have been nonlinearly modeled and 200 2-componets actual records have been considered for the IDA. The results reveal that at least 15 IDA steps are required to reduce fragility function error to less than 5% and 10 IDA steps are required to yield less than 10% error. In addition, it is revealed that a selection of 100 records is completely adequate to be certain to have an accurate fragility curve. It is concluded that at least 25 records are required to decrease fragility curve error to less than 5% and 15 records to have less than 10%. The closeness of fragility curve error variation for two models and in all limit states show that these results can be generalized to other RC frames.

Beginning in 2011 an international academic contest named as International Student Competition in Structural Optimization (ISCSO) has been organized by the authors to encourage undergraduate and graduate students to solve structural engineering optimization problems. During the past events on the one hand a unique platform is provided for a fair comparison of structural optimization algorithms; and on the other hand it is attempted to draw the attention of students to the interesting and joyful aspects of dealing with optimization problems. This year, after five online events successfully held with support and help of our advisory and scientific committee members from different universities all around the world, the authors decided to gather the test problems of the ISCSO in this technical report as an optimization test set. Beside the well -known traditional benchmark instances, the provided test set might also be used for further performance evaluation of future structural optimization algorithms.