• 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.

• 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.

• 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.

• 대한산업공학회지
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• 제39권2호
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• pp.90-98
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• 2013

The k-out-of-n system with mixed redundancy is defined as k-out-of-n system which both includes warm-standby and cold-standby components. In case that operating components in the system fail and the system needs quick transition of standby components to operation state, the k-out-of-n system with mixed redundancy is useful for decreasing system failure rate and operational cost. Reliability-Redundancy Optimization Problem (RROP) involves selection of components with multiple choices and redundancy levels for maximizing system reliability with constraints such as cost, weight, etc. A solution methodology by using harmony search algorithm for RROP of the k-out-of-n system with mixed redundancy to maximize system reliability was suggested in this study.

• 한국품질경영학회:학술대회논문집
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• 한국품질경영학회 2006년도 추계 학술대회
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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.

• 전기학회논문지
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• 제56권1호
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• pp.167-173
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• 2007

This paper describes a redundancy resolution based method for determining an optimal initial configuration of a humanoid robot for holding an object. There are three important aspects for a humanoid robot to be able to hold an object. Those three aspects are the reachability that guarantees the robot to reach the object, the stability that guarantees the robot to remain stable while moving or holding the object, and the manipulability that makes the robot manipulate the object dexterously. In this paper, a humanoid robot with 20 degrees of freedom is considered. The humanoid robot is kinematically redundant and has infinite number of solutions for the initial configuration problem. The complex three-dimensional redundancy resolution problem is divided into two simple two-dimensional redundancy resolution problems by incorporating the symmetry of the problem, robot's moving capability, and the geometrical characteristics of the given robot. An optimal solution with respect to the reachability, the stability, and the manipulability is obtained by solving these two redundancy resolution problems.

• 산업공학
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• 제25권2호
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• pp.153-162
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• 2012

The reliability is defined as a probability that a system will operate properly for a specified period of time under the design operating conditions without failure and it has been considered as one of the major design parameters in the field of industries. Reliability-Redundancy Optimization Problem(RROP) involves selec tion of components with multiple choices and redundancy levels for maximizing system reliability with constraints such as cost, weight, etc. However, in practice both active and cold standby redundancies may be used within a particular system design. Therefore, a redundancy strategy(active, cold standby) for each subsystem in order to maximize system reliability is considered in this study. Due to the nature of RROP, i.e. NP-hard problem, A Parallel Particle Swarm Optimization(PPSO) algorithm is proposed to solve the mathematical programming model and it gives consistently better quality solutions than existing studies for benchmark problems.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국제학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.234-239
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• 1993

Most of the control problem is for the redundant manipulators use the pseudo-inverse control, thit is, the redundancy is resolved by the pseudo-inverse of the Jacobian matrix and then the controller is designed based on this resolution. However, this pseudo-inverse control has some problems when the redundant robot repeats the cyclic tasks. This is because the pseudo-inverse resolution is a local solution that generates the different configurations of the robot arm for the same hand position. Therefore it is necessary to find the global solution that maintains the optimal configuration of the robot for the repetitive tasks. In this paper, we want to propose a redundancy resolution method by the optimal theory that uses the calculus of variation. The problem formulations are : first to convert the optimal resolution problem to an optimal control problem and then to resolve the redundancy using the necessary conditions of optimal control.

• 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.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2006년도 추계학술대회 논문집
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• pp.1198-1202
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• 2006

MTBF(Mean Time Between Failure)와 MTBSF(Mean Time Between Service Failure) are two representative quantitative reliability requirements for railway systems. There are the case that both of the two requirements are presented and the case that only one of them is presented in the specification of railway systems. we deal with the redundancy allocation problem to meet the two reliability requirements. The redundancy increases MTBSF while it decreases MTBF. 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 MTBF and MTBSF requirements.