Active Redundancy Allocation in Complex Systems by Using Different Optimization Methods

Caşcaval, Petru; Leon, Florin

doi:10.1007/978-3-030-28377-3_52

Cited by 6 publications

(6 citation statements)

References 16 publications

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“…where is the Lagrange multiplier. Thus, instead of maximizing the function R rs given by (20) within the cost constraint (21), we have to maximize the Lagrange function given by (22) without constraints. For this purpose, the following system with partial derivatives must be solved:…”

Section: Analytical Approach For Active Redundancymentioning

confidence: 99%

“…In Ref. 20, we introduced an original algorithm called \Pairwise Hill Climbing" (PHC) to address this issue. For our particular problem, a classic hill climbing method cannot be applied because simply adding components to the subsystems would likely cause the violation of the cost constraint.…”

Section: Pairwise Hill Climbingmentioning

confidence: 99%

“…In Ref. 20, it was discovered that the best results were given by a hybrid method that combined the analytical approach and PHC. However, real-valued evolutionary algorithms (EA) were also investigated to see whether they could provide the optimal solution by themselves.…”

Section: Relive | An Innovative Evolutionary Algorithmmentioning

confidence: 99%

“…19 This paper is an extended version of Ref. 20, in which the analytical method is explained in more detail and an original evolutionary algorithm (EA) is proposed that, unlike the approach previously used, seems to be able to solve large instances of the problem under consideration.…”

Section: Introductionmentioning

confidence: 99%

“…5, we mention the Pairwise Hill Climbing algorithm used in Ref. 20, while in Sec. 6, we describe a novel evolutionary algorithm, RELIVE, that combines global and local search.…”

Section: Introductionmentioning

confidence: 99%

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Optimization Methods for Redundancy Allocation in Large Systems

Leon

Caşcaval

Bǎdicǎ

2020

Vietnam J. Comp. Sci.

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This paper addresses the issue of optimal allocation of spare modules in large series-redundant systems in order to obtain a required reliability under cost constraints. Both cases of active and standby redundancy are considered. Moreover, for a subsystem with standby redundancy, two cases are examined: in the¯rst case, all the spares are maintained in cold state (cold standby redundancy) and, in the second one, to reduce the time needed to put a spare into operation when the active one fails, one of the spares is maintained in warm conditions. To solve this optimization problem, for the simpler case of active redundancy an analytical method based on the Lagrange multipliers technique is¯rst applied. Then the results are improved by using Pairwise Hill Climbing, an original¯ne-tuning algorithm. An alternative approach is an innovative evolutionary algorithm, RELIVE, in which an individual lives for several generations and improves its tness based on local search. These methods are especially needed in case of very large systems.

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Section: Analytical Approach For Active Redundancymentioning

confidence: 99%

Section: Pairwise Hill Climbingmentioning

confidence: 99%

Section: Relive | An Innovative Evolutionary Algorithmmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…5, we mention the Pairwise Hill Climbing algorithm used in Ref. 20, while in Sec. 6, we describe a novel evolutionary algorithm, RELIVE, that combines global and local search.…”

Section: Introductionmentioning

confidence: 99%

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Optimization Methods for Redundancy Allocation in Large Systems

Leon

Caşcaval

Bǎdicǎ

2020

Vietnam J. Comp. Sci.

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Redundancy Allocation Problem for a Continuous‐State Series‐Parallel System With Degrading Components: Electric Vehicle Application

Chen,

Yuan,

Bae

2024

Quality & Reliability Eng

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System reliability is a critical factor in designing complex engineering systems. Redundancy allocation problem (RAP) has attracted more interest owing to its wide scope of industrial applications for system reliability optimization. RAPs for binary‐state and multistate systems have been extensively studied. However, the redundancy allocation for continuous‐state systems composed of degrading components has not yet been fully explored. This study attempts to build the RAP for the continuous‐state parallel‐series system consisting of identical, independent, and nonrepairable components under active and cold‐standby redundancy strategies. The degradation of individual components in a system is continuous and modeled by the gamma process. The degradation at the system level is derived according to a deterministic structure function that relates the system degradation to the degradation of its components. Genetic algorithm and exhaustive search method are used to find the cost‐optimal redundancy design while satisfying a system reliability requirement. Series‐parallel lithium‐ion battery pack systems for electric vehicles (EVs) are used as an illustrative example to validate the proposed RAP and optimization model.

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01IP and QUBO: Optimization Methods for Redundancy Allocation in Complex Systems

Leon

Caşcaval

2019

2019 23rd International Conference on System Theory, Control and Computing (ICSTCC)

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Active Redundancy Allocation in Complex Systems by Using Different Optimization Methods

Cited by 6 publications

References 16 publications

Optimization Methods for Redundancy Allocation in Large Systems

Optimization Methods for Redundancy Allocation in Large Systems

Redundancy Allocation Problem for a Continuous‐State Series‐Parallel System With Degrading Components: Electric Vehicle Application

01IP and QUBO: Optimization Methods for Redundancy Allocation in Complex Systems

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