• Structural Engineering and Mechanics
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• v.52 no.6
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• pp.1209-1224
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• 2014

In Current paper, the voltages of patches optimization are carried out for minimizing the power consumption of piezoelectric patches and maximum vertical displacement of symmetrically FML panels using the modified multi-objective Elitist-Artificial Bee Colony (E-ABC) algorithm. The voltages of patches, panel length/width ratios, ply angles, thickness of metal sheets and edge conditions are chosen as design variables. The classical laminated plate theory (CLPT) is considered to model the transient response of the panel, and numerical results are obtained by the finite element method. The performance of the E-ABC is also compared with the PSO algorithm and shows the good efficiency of the E-ABC algorithm. To check the validity, the transient responses of isotropic and orthotropic panels are compared with those available in the literature and show a good agreement.

• Structural Engineering and Mechanics
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• v.55 no.6
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• pp.1223-1239
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• 2015

A method for structural damage identification based on Chaotic Artificial Bee Colony (CABC) algorithm is presented. ABC is a heuristic algorithm with simple structure, ease of implementation, good robustness but with slow convergence rate. To overcome the shortcoming, the tournament selection mechanism is chosen instead of the roulette mechanism and chaotic search mechanism is also introduced. Residuals of natural frequencies and modal assurance criteria (MAC) are used to establish the objective function, ABC and CABC are utilized to solve the optimization problem. Two numerical examples are studied to investigate the efficiency and correctness of the proposed method. The simulation results show that the CABC algorithm can identify the local damage better compared with ABC and other evolutionary algorithms, even with noise corruption.

• Structural Engineering and Mechanics
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• v.52 no.4
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• pp.755-765
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• 2014

In this present work, Artificial Bee Colony Algorithm (ABCA) is used to optimize the stacking sequences of simply supported antisymmetric laminated composite plates with criticial buckling load as the objective functions. The fibre orientations of the layers are selected as the optimization design variables with the aim to find the optimal laminated plates. In order to perform the optimization based on the ABCA, a special code is written in MATLAB software environment. Several numerical examples are presented to illustrate this optimization algorithm for different plate aspect ratios, number of layers and load ratios.

• Industrial Engineering and Management Systems
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• v.15 no.4
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• pp.324-334
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• 2016

Manufacturers and retailers are interested in how prices, promotions, discounts and other marketing variables can influence the sales and shares of the products that they produce or sell. Therefore, many models have been developed to predict the brand share. Since the customer choice models are usually used to predict the market share, here we use hybrid model of Probabilistic Neural Network and Artificial Bee colony Algorithm (PNN-ABC) that we have introduced to model consumer choice to predict brand share. The evaluation process is carried out using the same data set that we have used for modeling individual consumer choices in a retail coffee market. Then, to show good performance of this model we compare it with Artificial Neural Network with one hidden layer, Artificial Neural Network with two hidden layer, Artificial Neural Network trained with genetic algorithms (ANN-GA), and Probabilistic Neural Network. The evaluated results show that the offered model is outperforms better than other previous models, so it can be use as an effective tool for modeling consumer choice and predicting market share.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.23 no.3
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• pp.279-283
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• 2014

Recently, a topology algorithm based on the artificial bee colony algorithm (ABCA) has been proposed for static and dynamic topology optimization. From the results, the convergence rate of the algorithm was determined to be slightly slow. Therefore, we propose a new search method to improve the convergence rate of the algorithm using a chaotic map. We investigate the effect of the chaotic map on the convergence rate of the algorithm in static and dynamic topology optimization. The chaotic map has been applied to three cases, namely, employ bee search, onlooker bee search, and both employ bee as well as onlooker bee search steps. It is verified that the case in which the logistic function of the chaotic map is applied to both employ bee as well as onlooker bee search steps shows the best dynamic topology optimization, improved by 5.89% compared to ABCA. Therefore, it is expected that the proposed algorithm can effectively be applied to dynamic topology optimization to improve the convergence rate.

• Computers and Concrete
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• v.17 no.4
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• pp.435-453
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• 2016

The main purpose of this study is to perform optimum cost design of cut and cover RC shallow tunnels using Artificial bee colony and genetic algorithms. For this purpose, mathematical expressions of objective function, design variables and constraints for the design of cut and cover RC shallow tunnels were determined. By using these expressions, optimum cost design of the Trabzon Kalekapisi junction underpass tunnel was carried out by using the cited algorithms. The results obtained from the algorithms were compared with the results obtained from traditional design and remarkable saving from the cost of the tunnel was achieved.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.441-451
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• 2014

This article addresses an efficient heuristic-based approach to assign static shunt capacitors along radial distribution networks using the artificial bee colony algorithm. The objective function is adapted to enhance the overall system static voltage stability index and to achieve maximum net yearly savings. Load variations have been considered to optimally scope the fixed and switched capacitors required. The numerical results are compared with those obtained using recent heuristic methods and show that the proposed approach is capable of generating high-grade solutions and validated viability.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.23 no.3
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• pp.213-217
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• 2014

A hybrid search method based on the artificial bee colony algorithm (ABCA) with harmony search (HS) is suggested for finding a global solution in the field of optimization. Three cases of the suggested algorithm were examined for improving the accuracy and convergence rate. The results showed that the case in which the harmony search was implemented with the onlooker phase in ABCA was the best among the three cases. Although the total computation time of the best case is a little bit longer than the original ABCA under the prescribed conditions, the global solution improved and the convergence rate was slightly faster than those of the ABCA. It is concluded that the suggested algorithm improves the accuracy and convergence rate, and it is expected that it can effectively be applied to optimization problems with many design variables and local solutions.

• Membrane and Water Treatment
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• v.9 no.5
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• pp.363-371
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• 2018

In this work, it was investigated the usability of artificial bee colony (ABC) and genetic algorithm (GA) in modeling adsorption of Co(II) onto drinking water treatment sludge (DWTS). DWTS, obtained as inevitable byproduct at the end of drinking water treatment stages, was used as an adsorbent without any physical or chemical pre-treatment in the adsorption experiments. Firstly, DWTS was characterized employing various analytical procedures such as elemental, FT-IR, SEM-EDS, XRD, XRF and TGA/DTA analysis. Then, adsorption experiments were carried out in a batch system and DWTS's Co(II) removal potential was modelled via ABC and GA methods considering the effects of certain experimental parameters (initial pH, contact time, initial Co(II) concentration, DWTS dosage) called as the input parameters. The accuracy of ABC and GA method was determined and these methods were applied to four different functions: quadratic, exponential, linear and power. Some statistical indices (sum square error, root mean square error, mean absolute error, average relative error, and determination coefficient) were used to evaluate the performance of these models. The ABC and GA method with quadratic forms obtained better prediction. As a result, it was shown ABC and GA can be used optimization of the regression function coefficients in modeling adsorption experiments.

• Journal of Sensor Science and Technology
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• v.25 no.2
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• pp.91-102
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• 2016

The objective of this paper is to propose a heuristic algorithm to optimize the railway track maintenance scheduling, a NP-hard problem, by reflecting conditions of the actual field more quickly and easily. We develop the mechanism based on Binary Artificial Bee Colony (BABC) and Binary Harmony Search (BHS), and verify their performance through simulation experiments. Our proposed BABC and BHS mechanisms were applied to problems composed of 30, 60, 100, and 200 operations for railway track maintenance scheduling to carry out experiments and analysis. On comparing it with the results solved by CPLEX, it is found that the mechanism could present an optimal solution within limited time by user.