Computational Methods in Engineering

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In this paper, two algorithms have been developed for allocation and size determination of Active Power Filters (APF) in power systems. In the first algorithm, the objective is to minimize harmonic voltage distortion. The objective in the second algorithm is to minimize the new APF injection currents while satisfying harmonic standards. Genetic algorithm is proposed for these two optimization problems. The simulation results for an 18-bus system show the effectiveness of the genetic algorithm for these two optimization problems. Keywords: Genetic Algorithm, Active Power Filter, Harmonics, Allocation, Optimization

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Algorithmic skeleton has received attention as an efficient method of parallel programming in recent years. Using the method, the programmer can implement parallel programs easily. In this study, a set of efficient algorithmic skeletons is introduced for use in implementing parallel genetic algorithm (PGA).A performance modelis derived for each skeleton that makes the comparison of skeletons possible in order to select the best one for the application. The performance of the selected skeleton can be increased by specifying the virtual topology required by the appliation.This is a novel approach with no precedent. Nesting of skeletons used hereis another novelty of the study which has been employed only in few previous studies.

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This paper introduces an accurate, fast, and applicable method for optimization of slip surfaces in earth slopes. Using Genetic Algorithm (GA), which is one of the modern and non-classic optimization methods, in conjunction with the well -known Bishop applied method, the optimum slip surface in an earth slope is investigated and its corresponding lowest safety factor is determined. Investigations have shown that selection of appropriate variables to define and to solve the problem and determination of a good range for these variables have a profound effect on the speed of convergence in the problem. In the present study, appropriate variables have been defined for solving the problem in a way that the number of repetitions required to reach convergence are considerably reduced by up to 50% compared with other approaches. This has led to a drastic reduction in time and the memory required. The accuracy of the method is shown first by solving examples related to search for optimum failure surfaces of some homogenous, non-homogenous, and earth dam slopes and then by comparison of the results with those of other optimization techniques. In order to show the application of the present method in modern geotechnical engineering, a reinforced earth slope is studied and its failure surface is finally optimized

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Since there is no closed-form formula for designing TMD (Tuned Mass Damper) for nonlinear structures, some researchers have proposed numerical optimization procedures such as a genetic algorithm to obtain the optimal values of TMD parameters for nonlinear structures. These methods are based on determining the optimal values of TMD parameters to minimize the maximum response (e.g. inter story drift) of the controlled structure subjected to a specific earthquake record. Therefore, the performance of TMD that has been designed using a specific record strongly depends on the characteristics of the earthquake record. By changing the characteristics of the input earthquake record, the efficiency of TMD is changed and in some cases, it is possible that the response of the controlled structure is increased. To overcome the shortcomings of the previous researches, in this paper, an efficient method for designing optimal TMD on nonlinear structures is proposed, in which the effect of different ground motion records is considered in the design procedure. In the proposed method, the optimal value of the TMD parameters are determined so that the average maximum response (e.g. inter story drift) resulting from different records in the controlled structure is minimized. To illustrate the procedure of the propose method, the method is used to design optimal TMD for a sample structure. The results of numerical simulations show that the average maximum response of controlled structure resulting from different records is reduced significantly. Hence, it can be concluded that the proposed method for designing optimal TMD under different earthquakes is effective.

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In this paper, the solution of a non-linear model of Cell Manufacturing (CM) in certain and dynamic conditions is
studied, considering intracellular and extracellular costs, cell constructing costs, the cost of restoration and the cost of equipment
transportation per distance travelled. Since the number of cells in each stage of production is important, by optimizing the
number of cells, additional costs can be minimized. Therefore, the main objective of this study is to investigate the optimal
number of cells located. Bio-geographical Based Optimization (BBO) algorithm is applied in the CM for the first time in the
literature and the obtained results from this algorithm are compared with the results of well-known genetic algorithm. The results
shows the good performance of genetic algorithm. Finally, the conclusion and future research are provided.

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In this paper, a new method is proposed for fuzzy structural reliability analysis; it considers epistemic uncertainty arising from the statistical ambiguity of random variables. The proposed method, namely, fuzzy dynamic-directional stability transformation method, includes two iterative loops. An internal algorithm performs the reliability analysis using the dynamic-directional stability transformation method and an external algorithm performs the fuzzy analysis by applying the alpha-cut level optimization method based on the genetic algorithm. Implementation of the proposed method, which solves some nonlinear performance functions, indicates the efficiency and robustness of the dynamic-directional stability transformation method, as compared to other first order reliability methods.