• 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.

• 품질경영학회지
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• 제41권3호
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• pp.413-421
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• 2013

Purpose: System availability and life cycle cost are often used to evaluate the system performance and is influenced by the operation and maintenance characteristic. In this paper, we propose the method to improve life cycle cost and satisfy the target availability through redundancy allocation. Methods: We consider the redundancy is available at all items in multi level system. Thus, we assume that sub-assembly, module, components can be duplicated. Simulation and genetic algorithm are employed to optimize redundancy allocation. Results: Target availability is higher, the life cycle cost is increased. In addition, the items for redundancy are selected at higher level in multi level system if target availability is higher. Conclusion: We could know that target availability affects the duplication number of items and the selection of redundancy items. For further study, we will consider new optimization algorithms to compare with the proposed GA algorithm and improve optimization performance.

• 산업공학
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• 제23권2호
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• pp.147-155
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• 2010

Reliability allocation is defined as a problem of determination of the reliability for subsystems and components to achieve target system reliability. The determination of both optimal component reliability and the number of component redundancy allowing mixed components to maximize the system reliability under resource constraints is called reliability-redundancy allocation problem(RAP). The main objective of this study is to suggest a mathematical programming model and a hybrid parallel genetic algorithm(HPGA) for reliability-redundancy allocation problem that decides both optimal component reliability and the number of component redundancy to maximize the system reliability under cost and weight constraints. The global optimal solutions of each example are obtained by using CPLEX 11.1. The component structure, reliability, cost, and weight were computed by using HPGA and compared the results of existing metaheuristic such as Genetic Algoritm(GA), Tabu Search(TS), Ant Colony Optimization(ACO), Immune Algorithm(IA) and also evaluated performance of HPGA. The result of suggested algorithm gives the same or better solutions when compared with existing algorithms, because the suggested algorithm could paratactically evolved by operating several sub-populations and improve solution through swap, 2-opt, and interchange processes. In order to calculate the improvement of reliability for existing studies and suggested algorithm, a maximum possible improvement(MPI) was applied in this study.

• 한국국방경영분석학회지
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• 제26권2호
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• pp.143-158
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• 2000

This paper deals with the problem of redundancy allocation for the mixed reliability system in an optimal way. Two kinds of the reliability system are considered for optimal allocation of parallel redundancy. The problem is approached as the optimization problems using th standard method of dynamic programming(DP). The algorithm for solving the optimal redundancy allocation is proposed and then the DP algorithm is applied to two numerical examples such as maximization of reliability subject to an allowable cost-constraint and minimization of the total cost subject to the specified minimum reliability-constraint. A consequence of this study is that the developed computer program package can be applied to the optimal redundancy allocation for the mixed reliability system.

• 대한산업공학회지
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• 제43권2호
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• pp.135-146
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• 2017

This paper considers redundancy optimization problems of multi-level systems and reviews existing papers which proposed various optimization models and used different algorithms in this research area. Three different mathematical models are studied: Multi-level redundancy allocation (MRAP), multiple multi-level redundancy allocation, and availability-based MRAP models. Many meta-heuristics are applied to find optimal solutions in the several optimization problems. We summarized key idea of meta-heuristics applied to the existing MARP problems. Two extended models (MRAP with interval reliability of units and an integrated optimization problem of MRAP and preventive maintenance) are studied and further research ideas are discussed.

• 산업경영시스템학회지
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• 제9권14호
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• pp.45-48
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• 1986

This paper studies reliability growth model in redundancy allocation of Parallel-series system in which several series system is linked parallelly, The model is generalized by system redundancy of sub-system that have components redundancy. The stage of components in each sub-system is established differently. At the same time by assigned the different number of constraints to the sub-system, this paper deals with rather practical reliability growth model.

• Journal of Advanced Marine Engineering and Technology
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• 제38권8호
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• pp.1004-1009
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• 2014

The redundancy allocation problem has usually considered only the component redundancy at the lowest-level for the enhancement of system reliability. A system can be functionally decomposed into system, module, and component levels. Modular redundancy can be more effective than component redundancy at the lowest-level because in modular systems, duplicating a module composed of several components can be easier, and requires less time and skill. We consider a multi-level redundancy allocation problem in which all cases of redundancy for system, module, and component levels are considered. A tabu search of memory-based mechanisms that balances intensification with diversification via the short-term and long-term memory is proposed for its solution. To the best of our knowledge, this is the first attempt to use a tabu search for this problem. Our tabu search algorithm is compared with the previous genetic algorithm for the problem on the new composed test problems as well as the benchmark problems from the literature. Computational results show that the proposed method outstandingly outperforms the genetic algorithm for almost all test problems.

• 한국신뢰성학회지:신뢰성응용연구
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• 제1권1호
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• pp.1-8
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• 2001

Redundancy allocation problems have been considered at single-level systems and it may be the best policy in some specific situations, but not in general. With regards to reliability, it is most effective to allocate the lowest objects, because parallel-series systems are more reliable than series-parallel systems. However, the smaller and lower in the system an object is, the more time and accuracy are needed for duplicating it, and so, the cost can be decreased by using modular redundancy Therefore, providing redundancy at high levels like as modules or subsystems, can be more economical than providing redundancy at low levels or duplicating components. In this paper, the problem in which redundancy is allocated at all level in a series system is addressed, a mixed integer nonlinear programming model is presented and a genetic algorithm is proposed. An example illustrates the procedure.

• 품질경영학회지
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• 제47권4호
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• pp.701-711
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• 2019

Purpose: The problem of optimizing redundancy allocation in multi-level systems is considered when each item in a multi-level system has alternative items with the same function. The number of redundancy of multi-level system is allocated to maximize the reliability of the system under path set and cost limitation constraints. Methods: Based on cost limitation and path set constraints, a mathematical model is established to maximize system reliability. Particle swarm optimization is employed for redundant allocation and verified by numerical experiments. Results: Comparing the particle swarm optimization method and the memetic algorithm for the 3 and 4 level systems, the particle swarm optimization method showed better performance for solution quality and search time. Particularly, the particle swarm optimization showed much less than the memetic algorithm for variation of results. Conclusion: The proposed particle swarm optimization considerably shortens the time to search for a feasible solution in MRAP with path set constraints. PS optimization is expected to reduce search time and propose the better solution for various problems related to MRAP.

• 한국산학기술학회논문지
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• 제18권4호
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• pp.334-340
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• 2017

신뢰도는 열차, 비행기, 여객선과 같이 시스템에 한번 고장이 발생한 경우 치명적인 결과로 이어져 시스템에서 중요한 설계 요인으로 고려되어진다. 상당히 높은 신뢰도를 요구하는 시스템에서 시스템의 신뢰도를 향상시키는 방법에는 다양하게 있지만, 부품의 중복은 시스템 신뢰도를 향상시키기 위한 효율적인 방법으로 알려져 있다. 신뢰도를 높이기 위해 부품을 중복하는 경우에는 어떤 부품을 몇 개를 중복해야 하는지를 시스템 신뢰도 측면과 비용, 기타 설계자원 측면에서 고려하여야 한다. 본 연구에서는 직렬 구조를 가지는 다계층 시스템에 대한 중복할당의 방법을 다룬다. 다계층시스템에 대한 정의를 설명하고, 제약된 설계비용에서 시스템 신뢰도를 최대화하기 위한 중복 부품의 선정과 중복수량을 최적화하는 방법을 다룬다. 특히, 다계층 시스템에서 경로집합 중에 단 하나의 품목만 중복이 가능한 경우에 대해서 다루며, 유효한 해를 찾기 위한 방법을 제시한다. 최적화를 위해 뻐꾸기 탐색 알고리즘을 적용한다. 뻐꾸기 탐색 알고리즘에서는 다계층시스템의 중복할당 최적화를 위한 탐색절차, 이웃해의 탐색 방법, 해의 표현 등을 제시한다. 수치예제를 통해 기존에 유전알고리즘과 뻐꾸기 탐색 알고리즘의 성능을 비교한다.