• Industrial Engineering and Management Systems
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• 제15권4호
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• pp.364-373
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• 2016

Disassembly is one of the important activities in treating with the product at the End of Life time (EOL). Disassembly is defined as a systematic technique in dividing the products into its constituent elements, segments, sub-assemblies, and other groups. We concern with a Fuzzy Disassembly Line Balancing Problem (FDLBP) with multiple objectives in this article that it needs to allocation of disassembly tasks to the ordered group of disassembly Work Stations. Tasks-processing times are fuzzy numbers with triangular membership functions. Four objectives are acquired that include: (1) Minimization of number of disassembly work stations; (2) Minimization of sum of idle time periods from all work stations by ensuring from similar idle time at any work-station; (3) Maximization of preference in removal the hazardous parts at the shortest possible time; and (4) Maximization of preference in removal the high-demand parts before low-demand parts. This suggested model was initially solved by GAMS software and then using Genetic Algorithm (GA) in MATLAB software. This model has been utilized to balance automotive engine disassembly line in fuzzy environment. The fuzzy results derived from two software programs have been compared by ranking technique using mean and fuzzy dispersion with each other. The result of this comparison shows that genetic algorithm and solving it by MATLAB may be assumed as an efficient solution and effective algorithm to solve FDLBP in terms of quality of solution and determination of optimal sequence.

• Journal of Computational Design and Engineering
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• 제2권3호
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• pp.157-164
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• 2015

This paper discusses an optimization-based approach for the design of a product platform for industrial three-axis linear-type robots, which are widely used for handling objects in manufacturing lines. Since the operational specifications of these robots, such as operation speed, working distance and orientation, weight and shape of loads, etc., will vary for different applications, robotic system vendors must provide various types of robots efficiently and effectively to meet a range of market needs. A promising step toward this goal is the concept of a product platform, in which several key elements are commonly used across a series of products, which can then be customized for individual requirements. However the design of a product platform is more complicated than that of each product, due to the need to optimize the design across many products. This paper proposes an optimization-based fundamental framework toward the design of a product platform for industrial three-axis linear-type robots; this framework allows the solution of a complicated design problem and builds an optimal design method of fundamental features of robot frames that are commonly used for a wide range of robots. In this formulation, some key performance metrics of the robot are estimated by a reducedorder model which is configured with beam theory. A multi-objective optimization problem is formulated to represent the trade-offs among key design parameters using a weighted-sum form for a single product. This formulation is integrated into a mini-max type optimization problem across a series of robots as an optimal design formulation for the product platform. Some case studies of optimal platform design for industrial three-axis linear-type robots are presented to demonstrate the applications of a genetic algorithm to such mathematical models.

• 한국측량학회지
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• 제34권6호
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• pp.547-557
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• 2016

Due to threats caused by social disasters, operating surveillance devices are essential for social safety. CCTV, infrared cameras and other surveillance equipment are used to observe threats. This research proposes a method for searching for the optimum location of surveillance sensors. A GA (Genetic Algorithm) was used, since this algorithm is one of the most reasonable and efficient methods for solving complex non-linear problems. The sensor specifications, a DEM (Digital Elevation Model) and VITD (Vector Product Interim Terrain Data) maps were used for input data. We designed a chromosome using the sensor pixel location, and used elitism selection and uniform crossover for searching final solution. A fitness function was derived by the number of detected pixels on the borderline and the sum of the detection probability in the surveillance zone. The results of a 5-sensor and a 10-sensor were compared and analyzed.

• JSTS:Journal of Semiconductor Technology and Science
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• 제13권1호
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• pp.8-14
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• 2013

A low density parity check (LDPC) decoder provides a most powerful error control capability for mobile communication devices and storage systems, due to its performance being close to Shannon's limit. In this paper, we introduce an efficient overlapped LDPC decoding algorithm using a upper dual-diagonal parity check matrix structure. By means of this algorithm, the LDPC decoder can concurrently execute parts of the check node update and variable node update in the sum-product algorithm. In this way, we can reduce the number of clock cycles per iteration as well as reduce the total latency. The proposed decoding structure offers a very simple control and is very flexible in terms of the variable bit length and variable code rate. The experiment results show that the proposed decoder can complete the decoding of codewords within 70% of the number of clock cycles required for a conventional non-overlapped decoder. The proposed design also reduces the power consumption by 33% when compared to the non-overlapped design.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 D
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• pp.2726-2728
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• 2001

This paper describes an optimal synthesis method of binary neural network(BNN) for an approximation problem of a circular region using a newly proposed learning algorithm[7] Our object is to minimize the number of connections and neurons in hidden layer by using a Newly Expanded and Truncated Learning Algorithm(NETLA) for the multilayer BNN. The synthesis method in the NETLA is based on the extension principle of Expanded and Truncated Learning(ETL) and is based on Expanded Sum of Product (ESP) as one of the boolean expression techniques. And it has an ability to optimize the given BNN in the binary space without any iterative training as the conventional Error Back Propagation(EBP) algorithm[6] If all the true and false patterns are only given, the connection weights and the threshold values can be immediately determined by an optimal synthesis method of the NETLA without any tedious learning. Futhermore, the number of the required neurons in hidden layer can be reduced and the fast learning of BNN can be realized. The superiority of this NETLA to other algorithms was proved by the approximation problem of one circular region.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 2005년도 춘계공동학술대회 발표논문
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• pp.715-722
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• 2005

Disassembly scheduling is the problem of determining the quantity and timing of disassembling used products while satisfying the demand of their parts or components over a planning horizon. The case of single product type with assembly structure is considered for the objective of minimizing the sum of disassembly operation and inventory holding costs. In particular, the resource capacity constraint is explicitly considered. The problem is formulated as an integer programming model, and a two-stage heuristic with construction and improvement algorithms is suggested in this paper. To show the performance of the heuristic, computational experiments are done on a number of randomly generated problems, and the test results show that the algorithm can give near optimal solutions within a very short amount of computation time.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1997년도 추계학술대회 학술발표 논문집
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• pp.287-290
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• 1997

신경회로망은 높은 정확도의 학습 결과를 제시하는 장점을 가지고 있어서 패턴 인식을 포함한 여러 분야에서 널리 사용되어지고 있다. 그러나 신경회로망의 설계에 있어 최적의 뉴런과 층의 개수, 그리고 그 연결 등의 기하학적 해답을 제시하기가 어렵고, 서은이 우수하다고 알려진 역전파 학습 알고리즘도 오차가 없는 완벽한 학습 결과를 제시하지 못하며, 상당히 많은 학습 시간이 걸린다는 단점들을 가지고 있다. 이러한 단점들을 극복하기 위해 선형 신경회로망을 합성하는 새로운 방법을 제안하는데, 이진 함수 최소화(binary function minimization)과정을 거친 minimal-sum-of-product(MSP)를 통해서 이진 클래스 패턴(binary class pattem)을 표현 함으로써 오차가 없는 학습 결과를 얻을 수 있으며, 학습에 필요한 패턴과 학습에 걸리는 시간도 대폭 줄일수 있다. 본 논문에서는 유전자 알고리즘을 이용하여 선형 신경회로망을 합성하는 방법을 제안하며, 여러 가지 예제를 통해 제안한 방법의 우수성을 보인다.

• 정보학연구
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• 제10권2호
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• pp.47-64
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• 2007

Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. Accurate predictions of software release times, and estimation of the reliability and availability of a software product require quantification of a critical element of the software testing process : test coverage. This model called enhanced non-homogeneous poission process(ENHPP). In this paper, exponential coverage and S-coverage model was reviewed, proposes the exponentiated exponential coverage reliability model, which maked out efficiency substituted for gamma and Weibull model(2 parameter shape illustrated by Gupta and Kundu(2001). In this analysis of software failure data, algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE statistics for the sake of efficient model, was employed.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2006년도 하계종합학술대회
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• pp.999-1000
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• 2006

The LDPC Code is focusing a powerful FEC(Forward Error Correction) codes for 4G Mobile Communication system. LDPC codes are used minimizing channel errors by modeling AWGN Channel as VDSL system. The performance of LDPC code is better than that of turbo code in long code word on iterative decoding algorithm. LDPC code are encoded by sparse parity check matrix. there are decoding algorithms for a LDPC code, Bit Flipping, Message passing, Sum-Product. Because LDPC Codes use low density parity bit, mathematical complexity is low and relating processing time becomes shorten.

• 스마트미디어저널
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• 제2권2호
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• pp.39-43
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• 2013

본 논문은 오류정정부호의 하나인 LDPC 패리티검사 행렬을 생성 하는 방법에 관한 논문으로 또 다른 오류정정부호의 하나인 길쌈부호를 이용하여 LDPC 패리티검사 행렬을 생성하면 터보부호처럼 LDPC 부호에서도 다양한 부호율을 쉽게 얻을 수 있다는 장점을 가진다. 또한 복호기에서 LDPC에서의 복호방식 뿐 아니라 길쌈부호의 복호방식인 비터비알고리즘도 적용할 수 있는 장점을 가진다. 또한 보통의 오류정정부호의 경우 프레임크기가 커야 오류정정성능이 안정적으로 나오는데, 새로 제시하는 방식을 통해 프레임크기가 작은 부호의 경우에도 성능열화를 어느 정도 막을 수 있다.