• 한국정밀공학회지
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• 제15권12호
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• pp.72-80
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• 1998

In this study, a design approach based on genetic algorithm is proposed to solve the manufacturing cell design problem considering alternative process plans and alternative machines. The problem is formulated as a 0-1 integer programming model which considers several manufacturing parameters, such as demand and processing time of part, machine capacity, manufacturing cell size, and the number of machines in a machine cell. A genetic algorithm is used to determine process plan for each part, part family and machine cell simultaneously.

• 한국컴퓨터산업학회논문지
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• 제6권5호
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• pp.813-820
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• 2005

대체공정을 고려한 Job Shop 일정계획을 수립하기 위한 유전알고리즘을 개발하기 위하여 다음과 같이 유전알고리즘 효율분석을 실시하였다. 첫째, 대체공정을 고려한 job shop 일정계획을 수립하기 위한 유전 알고리즘을 제시하고 둘째, 전통적인 job shop 일정계획에 대한 벤치마크 문제에 대해 유전 알고리즘의 타당성을 확인하고 셋째, Park[3] 문제에 대해 유전알고리즘과 작업배정규칙을 적용한 결과를 비교하였다.

• 전기학회논문지P
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• 제64권4호
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• pp.315-320
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• 2015

Proposal algorithm in this paper introduced cells, units of router group, for distributed processing of previous genetic algorithm. This paper presented ways to reduce search delay time of overall network through cell-based genetic algorithm. As a result of performance analysis comparing with existing genetic algorithm through experiments, the proposal algorithm was verified superior in terms of costs and delay time. Furthermore, time for routing an alternative path was reduced in proposal algorithm, in case that a network was damaged in existing optimal path algorithm, Dijkstra algorithm, and the proposal algorithm was designed to route an alternative path faster than Dijkstra algorithm, as it has a 2nd shortest path in cells of the damaged network. The study showed that the proposal algorithm can support routing of alternative path, if Dijkstra algorithm is damaged in a network.

• 산업경영시스템학회지
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• 제39권3호
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• pp.83-89
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• 2016

The group formation problem of the machine and part is a critical issue in the planning stage of cellular manufacturing systems. The machine-part grouping with alternative process plans means to form machine-part groupings in which a part may be processed not only by a specific process but by many alternative processes. For this problem, this study presents an algorithm based on self organizing neural networks, so called SOM (Self Organizing feature Map). The SOM, a special type of neural networks is an intelligent tool for grouping machines and parts in group formation problem of the machine and part. SOM can learn from complex, multi-dimensional data and transform them into visually decipherable clusters. In the proposed algorithm, output layer in SOM network had been set as one-dimensional structure and the number of output node has been set sufficiently large in order to spread out the input vectors in the order of similarity. In the first stage of the proposed algorithm, SOM has been applied twice to form an initial machine-process group. In the second stage, grouping efficacy is considered to transform the initial machine-process group into a final machine-process group and a final machine-part group. The proposed algorithm was tested on well-known machine-part grouping problems with alternative process plans. The results of this computational study demonstrate the superiority of the proposed algorithm. The proposed algorithm can be easily applied to the group formation problem compared to other meta-heuristic based algorithms. In addition, it can be used to solve large-scale group formation problems.

• 품질경영학회지
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• 제43권1호
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• pp.31-42
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• 2015

Purpose: System consists of a lot of units with coherent function. In design phase, various units could be considered with the same function. In this study, we consider the alternative units with the same function and redundancy allocation to maximize system reliability in multi level system. Methods: The redundancy allocation problem with the alternative units in multi level system is formulated. Memetic algorithm(MA) is proposed to optimize the redundancy allocation problem. In addition, the performance of the proposed algorithm is explained by a numerical experiment. Results: MA showed better results than genetic algorithm(GA) and the convergence of the solutions in MA was also faster than GA. In addition, we could know from experiment that system reliability is increased and the chosen unit for redundancy allocation is changed if cost limit is increased. Conclusion: The chose unit for redundancy allocation is changed as resource constraints. It means we need to consider the alternative units in system design. In the future, we need to consider various problem related to redundancy allocation in multi level system and develop the better method to enhance search performance.

• 대한전자공학회논문지TC
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• 제41권5호
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• pp.11-18
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• 2004

본 논문에서는 보다 신뢰성이 요구되는 MPLS 망을 위한 복구경로 할당에 대하여 새로운 알고리즘을 제안한다. 제안 알고리즘은 QoS 파라미터에 근거하여 사용자 트랙픽을 분류한다. 실시간 트래픽과 비실시간 트래픽의 우선 순위를 부여하여 예비경로를 할당한다. 제안된 알고리즘은 이러한 우선순위 기법을 통하여 상대적으로 고가인 양질의 서비스를 요구하는 실시간 트래픽의 오류에 대비하여 보다 신뢰성이 보장되는 복구경로를 제공한다. 또한 복구 경로로 설정시 링크 사용에 의해 발생되는 네트워크 자원의 부족 문제해결을 개선 향상시킬 수 있다. 제안된 알고리즘은 프로그램 툴을 이용한 시뮬레이션을 통하여 기존 알고리즘과 비교 분석되었으며 그 결과 유효성을 확인하였다. 또한 복규율에서 기존방식에 비해 89%에서 98%로 9% 개선효과가 있다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2015년도 춘계학술대회
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• pp.632-635
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• 2015

본 논문에서는 제안한 알고리즘은 이전 유전 알고리즘의 분산처리를 위해 라우터 그룹 단위인 셀을 도입하였다. 셀 단위로 유전 알고리즘을 시행하여 전체 네트워크의 탐색 지연시간을 줄이는 방법을 제시하였다. 실험을 통하여 기존 유전 알고리즘과의 성능 분석에 대한 결과는 비용면에서나 지연시간면에서 제안한 알고리즘이 우위에 있는 것으로 나타났다. 또한, 기존 최적경로 알고리즘인 Dijkstra 알고리즘에서 네트워크가 손상되었을 경우 제안한 알고리즘에는 대체 경로 설정의 연산시간이 단축되었으며 손상된 네트워크의 셀 안에서 2순위의 경로를 가지고 있으므로 Dijkstra 알고리즘보다 신속하게 대체경로를 설정하도록 설계되었다. 이는 제안한 알고리즘이 네트워크상에서 Dijkstra 알고리즘이 손상되었을 경우 대체 경로설정을 보완할 수 있음을 확인하였다.

• 대한산업공학회지
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• 제29권3호
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• pp.213-221
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• 2003

In this paper, we consider a multi-objective part-machine grouping problem, in which part types have several alternative part routings and each part routing has a machining sequence. This problem is characterized as optimally determining part type sets and its corresponding machine cells such that the sum of inter-cell part movements and the sum of machine workload imbalances are simultaneously minimized. Due to the complexity of the problem, a two-stage heuristic algorithm is proposed, and experiments are shown to verify the effectiveness of the algorithm.

• 한국경영과학회지
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• 제30권3호
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• pp.41-54
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• 2005

In this paper, we consider a multi-objective machine cell formation problem. This problem Is characterized as determining part route families and machine cells such that total sum of inter-ceil part movements and maximum machine workload imbalance are simultaneously minimized. Together with the objective function, alternative part routes and the machine sequences of part routes are considered In grouping Part route families. Due to the complexity of the problem, a two-phase heuristic algorithm is proposed. And we developed an n-stage look-ahead heuristic algorithm that generalizes the roll-out algorithm. Computational experiments were conducted to verify the performance of the algorithm.

• 한국경영과학회지
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• 제30권3호
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• pp.55-65
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• 2005

In recent manufacturing systems, most jobs may have several process plans, such as alternative sequence of operations, alternative machine etc. A few researches have addressed the necessity for the integration of process planning and scheduling function for efficient use of manufacturing resources. But the integration problem is very difficult and complex. Many prior researches considered them separately or sequentially. It introduces overlapping or partial duplications in solution efforts. In this paper, Integration problem of jobs with multiple process plans in a job shop environment Is addressed. In order to achieve an efficient integration between process planning and scheduling by taking advantage of the flexibility that alternative process plans offer, we designed GA(Genetic Algorithm)-based scheduling method. The performance of proposed GA is evaluated through comparing integrated scheduling with separated scheduling in real world company with alternative machines and sequences of operations. Also, a couple of benchmark problems are used to evaluate performance. The integrated scheduling method in this research can be effectively epplied to the real case.