• Proceedings of the Acoustical Society of Korea Conference
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• 1998.06c
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• pp.107-110
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• 1998

본 논문은 DTW(Dynamic Time Warping)을 이용한 음성인식에서 표준패턴(reference patterns)으로 사용되는 벡터열을 GA(Genetic Algorithm)을 이용하여 보다 적응된 패턴의 벡터열로 생성하는 방법을 제시한다. 본 논문의 필요성은 다음과 같다. 음성인식의 주요한 엔진들 중에 하나로 DTW가 사용된다[1]. DTW는 표준패턴과 시험패턴(test patterns)간의 최적 경로(optimal path)를 찾아내어 가장 유사한 패턴을 찾아내는 방법을 말한다. 그러나 음성은 같은 발음에 대해서도 사람의 발성 길이와 목의 상태 등에 따라 다양한 패턴으로 나타나며 동일 화자의 같은 어휘도 시간과 환경에 따라 변한다. 따라서 이러한 음성의 동적 특성에 적응하는 방법이 필요하다. 본 논문은 이러한 문제에 대한 해결 방법으로 GA를 이용하여 보다 적합하고 적응적인 표준 패턴을 생성시켜 적응하는 방법을 개발하였다.

• IE interfaces
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• v.24 no.4
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• pp.362-372
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• 2011

Container pick-up scheduling problem is to minimize the total container handling time, which consists of the traveling distance and the setup time of yard cranes in a container yard. Yard cranes have to pick-up the containers which are stacked in the yard-bays to satisfy the work schedule requirement of quay crane, which loads and unloads containers on or from container ships. This paper allows the movement of multiple yard cranes among storage blocks. A mixed integer programming model has been formulated and a genetic algorithm (GA) has been proposed to solve problems of large sizes. Computational results show that the proposed GA is an effective method.

• IE interfaces
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• v.17 no.spc
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• pp.28-36
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• 2004

The main purpose of this study is to find out the optimal solution of the vehicle routing problem considering heterogeneous vehicle(s), double-trips, and multi depots. This study suggests a mathematical programming model with new numerical formula which considers the amount of delivery and sub-tour elimination and gives optimal solution by using OPL-STUDIO(ILOG). This study also suggests modified genetic algorithm which considers the improvement of the creation method for initial solution, application of demanding point, individual and last learning method in order to find excellent solution, survival probability of infeasible solution for allowance, and floating mutation rate for escaping from local solution. The suggested modified genetic algorithm is compared with optimal solution of the existing problems. We found the better solution rather than the existing genetic algorithm. The suggested modified genetic algorithm is tested by Eilon and Fisher data(Eilon 22, Eilon 23, Eilon 30, Eilon 33, and Fisher 10), respectively.

• Journal of Korean Institute of Industrial Engineers
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• v.30 no.3
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• pp.250-260
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• 2004

This study considers a linear connected-(r,s)-out-of-(m,n):F lattice system whose components are ordered like the elements of a linear (m,n )-matrix. We assume that all components are in the state 1 (operating) or 0 (failed) and identical and s-independent. The system fails whenever at least one connected (r,s)-submatrix of failed components occurs. The purpose of this paper is to present an optimization scheme that aims at minimizing the expected cost per unit time. To find the optimal threshold of maintenance intervention, we use a genetic algorithm for the cost optimization procedure. The expected cost per unit time is obtained by Monte Carlo simulation. The sensitivity analysis to the different cost parameters has also been made.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.1
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• pp.54-60
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• 2001

In this paper, a shape-based block layout (SBL) approach is presented to solve the facility layout problem with unequal-area and fixed shapes. The SBL approach employs hybrid genetic algorithm (Hybrid-GA) to find a good solution and the concept of bay structure is used. In the typical facility layout problem with unequal area and fixed shapes, the given geometric constraints of unequal-area and fixed shapes are mostly approximated to original shape by aspect ratio. Thus, the layout results require extensive manual revision to create practical layouts and it produces irregular building shapes and too much unusable spaces. Experimental results show that a SBL model is able to produce better solution and to create more practical layouts than those of existing approaches.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.1
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• pp.1-16
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• 1998

The zone clustering problem arising from several area such as deciding the optimal location of ambient measuring stations is to devide the 2-dimensional area into several sub areas in which included individual zone shows simimlar properties. In general, the optimal solution of this problem is very hard to obtain. Therefore, instead of finding an optimal solution, the generation of near optimal solution within the limited time is more meaningful. In this study, the combination of a genetic algorithm and the modified k-means method is used to obtain the near optimal solution. To exploit the genetic algorithm effectively, a representation of chromsomes and appropriate genetic operators are proposed. The k-means method which is originally devised to solve the object clustering problem is modified to improve the solutions obtained from the genetic algorithm. The experiment shows that the proposed method generates the near optimal solution efficiently.

• Korean Management Science Review
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• v.14 no.1
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• pp.67-76
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• 1997

The most research on facility layout problems ignored the actual shapes of activity spaces and the aisles between activities. In many cases, the research also ignored the actual shape of building where the activities are to be arranged. In this paper, We present a block based layout technique that applies a genetic algorithm to search for a very good facility layout with horizontal aisles. From the extensive experiments for two different cases with respect to the shape of activity space, it was found that the proposed method generated better layouts than the ones obtained by applying Tam's algorithm in all test problems. The proposed algorithm showed about 10% improvement of performance on the average. We determined the best combination of the reproduction rule and the genetic operators with their probabilities for each test problem through the experiment.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2513-2515
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• 2005

Recently genetic algorithm techniques have widely used in adaptive and control schemes for production systems. However, generally it costs a lot of time for leaming in the case applied in control system. Furthermore, the physical meaning of genetic algorithm constructed as a result is not obvious. And this method has been used as a learning algorithm to estimate the parameter of a genetic algorithm used for identification of the process dynamics of Butter-Worth analog filter and it was shown that this method offered superior capability over the genetic algorithm. A genetic algorithm is used to solve the parameter identification problem for linear and nonlinear digital filters. This paper goal estimate Butter-Worth analog filter parameter using the genetic algorithm.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.78-80
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• 2005

The load flow calculation is one of the most critical issues in electrical power systems. Generally, load flow has been calculated by Gauss-Seidel method and Newton-Raphson method but these methods have some problems such as non-convergence due to heavy load and initial value. In this paper, to overcome such problems, the power flow is calculated by genetic algorithm. At the heavy load, the solution for problem can not be obtained by the Newton-Raphson method. However, it can be solved in case of using genetic algorithm. In this paper, the strong point of this method would be demonstrated in application to an example system.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.15-17
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• 2005

Recently genetic algorithm techniques have widely used in adaptive and control schemes for production systems. However, generally it costs a lot of time for learning in the case applied in control system. Furthermore, the physical meaning of genetic algorithm constructed as a result is not obvious. And this method has been used as a learning algorithm to estimate the parameter of a genetic algorithm used for identification of the process dynamics of nonlinear IIR filter and it was shown that this method offered superior capability over the genetic algorithm. A genetic algorithm is used to solve the parameter identification problem for linear and nonlinear digital filters. This paper goal estimate nonlinear IIR filter parameter using the genetic algorithm.