• Journal of Korea Society of Industrial Information Systems
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• v.25 no.6
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• pp.159-169
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• 2020

A cold chain logistics (CCL) model for chilled food (-1℃ to 8℃) distributed in China was developed in this study. The CCL model consists of a distribution center (DC) and distribution target points (DT). The objective function of the CCL model is to minimize the total distribution routes of all distributors. To find the optimal result of the objective function, the hybrid genetic algorithm (HGA) approach is proposed. The HGA approach was constructed by combining the improved K-means and genetic algorithm (GA) approaches. In the case study, three scenarios were considered for the CCL model based on the distribution routes and the available distance, and they were solved using the proposed HGA approach. Analysis results showed that the distribution costs and mileage were reduced by approximately 19%, 20% and 16% when the proposed HGA approach was used.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.4
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• pp.91-97
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• 2011

In this paper we present an approach to the structure identification based on genetic algorithm and to the parameter identification by hybrid learning method in neuro-fuzzy-genetic hybrid system in order to predicate the Mackey-Glass Chaotic time series. In this scheme the basic idea consists of two steps. One is the construction of a fuzzy rule base for the partitioned input space via genetic algorithm, the other is the corresponding parameters of the fuzzy control rules adapted by the backpropagation algorithm. In an attempt to test the performance the proposed system, three patterns, x(t-3), x(t-6) and x(t-9), was prepared according to time interval. It was through lots of simulation proved that the initial small error of learning owed to the good structural identification via genetic algorithm. The performance was showed in Table 2.

• Communications for Statistical Applications and Methods
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• v.19 no.1
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• pp.65-75
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• 2012

In setting an experimental design for the prediction outside the experimental region (extrapolation design), it is natural for the experimenter to be very careful about the validity of the model for the design because the experimenter is not certain whether the model can be extended beyond the design region or not. In this paper, a hybrid constrained type approach was adopted in dealing model uncertainty as well as the prediction error using the three basic principles available in literature, maxi-min, constrained, and compound design. Furthermore, the effect of the distance of the extrapolation design point from the design region is investigated. A search algorithm was used because the classical exchange algorithm was found to be complex due to the characteristic of the problem.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.5
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• pp.577-582
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• 2012

If the mobile station requests the channel allocation in mobile networks, switching center is assigned a channel to mobile station that belong to each base station. Channel allocation schemes is a fixed channel allocation, dynamic channel allocation and a hybrid approach that combines the two forms. To assign a frequency well to use resources efficiently to provide quality service to our customers. In this paper, we proposed method to assign frequencies to minimize interference between channels and to minimizes the number of searching time. The proposed method by the genetic algorithm to improve accuracy and efficiency of the verification steps and reproduction stages were used. In addition, the proposed method by comparing with other methods showed that proposed method is better through the simulations.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.05a
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• pp.83-86
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• 2001

In this paper, it study about the image filter applied the hybrid fuzzy membership function to the neuro-fuzzy system. Here, this system applys the genetic algorithm in order to obtain the optimal image as the iteration carry for making the data value in the error. It is removed the included noise in an image using the proposed image filter and compared the proposed image filter performance with the other filters using MATLAB. And it is found that the proposed filter performance is superior to the other filters which has the similar structure through the images. To show the superior ability, it is compared with MSE and SNR for images.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.20 no.4
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• pp.390-395
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• 2009

Design and optimization of a broadband meander-line twist reflector was performed for X-band application. Based on the equivalent transmission line model, the polarization twist performance was evaluated. Genetic analysis, particles swarm, and hybrid swarm optimizations were employed to obtain the optimized geometrical parameters. The optimized design exhibits low cross-polarization level below - 25 dB between 8.45 and 11.38 GHz. The polarization twist loss was below 0.2 dB. Comparison between computed and simulated results was also discussed.

• Smart Media Journal
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• v.10 no.3
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• pp.23-30
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• 2021

Although the manufacturing time series data clustering technique is an important grouping solution in the field of detecting and improving manufacturing large data-based equipment and process defects, it has a disadvantage of low accuracy when applying the existing static data target clustering technique to time series data. In this paper, an evolutionary computation-based time series cluster analysis approach is presented to improve the coherence of existing clustering techniques. To this end, first, the image shape resulting from the manufacturing process is converted into one-dimensional time series data using linear scanning, and the optimal sub-clusters for hierarchical cluster analysis and split cluster analysis are derived based on the Pearson distance metric as the target of the transformation data. Finally, by using a genetic algorithm, an optimal cluster combination with minimal similarity is derived for the two cluster analysis results. And the performance superiority of the proposed clustering is verified by comparing the performance with the existing clustering technique for the actual manufacturing process image.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.40 no.5
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• pp.298-311
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• 2003

Iterative Fourier transform algorithm, (IFTA) is tile iterative numerical algorithm for the design of the diffractive optical elements (DOE), by which the phase distribution of a DOE converges on a local optimal solution. The convergence of IFTA depends on several factors 3s initial phase distribution, the structure of the degree of freedom on the observation plane, and the values of internal parameters. In this paper, we analyze tile dependence of the convergence of IFTA on an internal parameter of IFTA, the relaxation parameter, and propose a new hybrid scheme of genetic algorithm and IFTA to obtain more accurate solution.

• Journal of Digital Convergence
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• v.10 no.9
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• pp.375-381
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• 2012

If a mobile station requests a channel allocation in its mobile networks, the switching center assigns a channel to a mobile station that belongs to each base station. There are three kinds of channel allocation schemes; a fixed channel allocation, a dynamic channel allocation and a hybrid combination of these two forms. In assigning a good frequency, it is our intention to provide quality service to our customers as well as to use resources efficiently. This paper proposes methods of assigning frequencies that minimize interference between channels and that also minimize the amount of searching time involved. In this paper, we propose an algorithm to per specific equipment, regardless of the number of channels that can be used as a general-purpose system, such as base stations, control stations, central office model is proposed, the existing operators manner similar to the fixed channel allocation based statistics and assigned when the conventional method and the improved method is proposed. Different ways and compared via simulations to verify the effectiveness of the proposed approach.

• The Transactions of the Korea Information Processing Society
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• v.6 no.4
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• pp.959-968
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• 1999

several papers have reported that parallel heuristics or hybrid approaches combining several heuristics can get better results. However, the parallelization and hybridization of any search methods on the single CPU type computer need enormous computation time. that case, we need more elegant combination method. For this purpose, we propose Fast Model of Parallel Heuristics(FMPH). FMPH is based on the island model of parallel genetic algorithms and takes local search to the elite solution obtained form each island(sub group). In this paper we introduce how can we adapt FMPH to the job-shop scheduling problem notorious as the most difficult NP-hard problem and report the excellent results of several famous benchmark problems.