• Journal of Korean Society for Quality Management
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• v.43 no.1
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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.

• IE interfaces
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• v.23 no.2
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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.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.8
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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.

• Journal of the military operations research society of Korea
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• v.26 no.2
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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.

• Journal of Korean Institute of Industrial Engineers
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• v.43 no.2
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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.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.2
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• pp.225-232
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• 2014

The traditional RAP (Redundancy Allocation Problem) of complex systems has considered only the redundancy of subsystem with homogeneous components. In this paper we extend it as a RAP of complex systems with heterogeneous components which is more flexible than the case of homogeneous components. We model this problem as a nonlinear integer programming problem, find its optimal solution by tabu search, and suggest an example of the efficient reliability design with heterogeneous components. In order to improve the quality of the solution of the tabu search, we suggest a modified tabu search to employ an adaptive procedure (1-opt or 2-opt exchange) to generate the efficient neighborhood solutions. Computational results show that our modified procedure obtains better solutions as the size of problem increases from 30 to 50, even though it requires rather more computing time. With some adjustment of the parameters of the proposed method, it can be applied to the optimal reliability designs of complex systems of ships.

• Proceedings of the Korean Society for Quality Management Conference
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• 2006.11a
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• pp.105-109
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• 2006

MTTR and MTBSF are two representative quantitative maintainability and reliability requirements for railway systems. we deal with the redundancy allocation problem to satisfy the two requirements. The redundancy increases MTBSF and changes MTTR. Parallel redundancy and the exponential lifetime distribution of components are considered for the series systems. Mathematical model and example are presented for the redundancy optimization problem of minimizing the cost subjecting to MTTR and MTBSF requirements.

• International Journal of Reliability and Applications
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• v.12 no.2
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• pp.79-94
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• 2011

Redundancy-reliability allocation problems in multi-stage series-parallel systems are addressed in this study. Fuzzy programming techniques are proposed for finding satisfactory solutions. First, a multi-objective programming model is formulated for simultaneously maximizing system reliability and minimizing system total cost. Due to the nature of uncertainty in the problem, the fuzzy set theory and technique are used to convert the deterministic multi-objective programming model into a fuzzy nonlinear programming problem. A heuristic method is developed to get satisfactory solutions for the fuzzy nonlinear programming problem. A Pareto optimal solution is found with maximal degree of satisfaction from the interception area of fuzzy sets. A case study that is related to the electronic control unit installed on aircraft engine over-speed protection system is used to implement the developed approach. Results suggest that the developed fuzzy multi-objective programming model can effectively resolve the fuzzy and uncertain problem when design goals and constraints are not clearly confirmed at the initial conceptual design phase.

• Industrial Engineering and Management Systems
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• v.4 no.1
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• pp.94-101
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• 2005

This paper presents the first known application of a meta-heuristic algorithm, variable neighbourhood descent (VND), to the redundancy allocation problem (RAP). The RAP, a well-known NP-hard problem, has been the subject of much prior work, generally in a restricted form where each subsystem must consist of identical components. The newer meta-heuristic methods overcome this limitation and offer a practical way to solve large instances of the relaxed RAP where different components can be used in parallel. The variable neighbourhood descent method has not yet been used in reliability design, yet it is a method that fits perfectly in those combinatorial problems with potential neighbourhood structures, as in the case of the RAP. A variable neighbourhood descent algorithm for the RAP is developed and tested on a set of well-known benchmark problems from the literature. Results on 33 test problems ranging from less to severely constrained conditions show that the variable neighbourhood descent method provides comparable solution quality at a very moderate computational cost in comparison with the best-known heuristics. Results also indicate that the VND method performs with little variability over random number seeds.

• Journal of Applied Reliability
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• v.1 no.1
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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.