Genetic algorithms for reliability design problems

Hsieh, Yi-Chih; Chen, Ta-Cheng; Bricker, Dennis L.

doi:10.1016/s0026-2714(98)00028-6

Cited by 152 publications

(102 citation statements)

References 22 publications

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“…To the best of the authors' knowledge, MINLP problems are generally solved by heuristic algorithms as an exhaustive search of the optimum solution is usually impractical. One of the most widely used algorithms is the so-called GA (Genetic Algorithm) [11] due to the following advantages: (i) the encoding scheme (binary or decimal encoding) in the GA leads to the flexibility to represent both continuous and discrete design variables; and (ii) the search in the solution space for optimal solutions can be very efficient due to the use of fitness evaluation and genetic operator functions. Although the GA is employed to solve the top-level RAP, the computational cost for function evaluations can be negligible since the system LCC and resilience are computed through the evaluation of analytic models.…”

Section: Genetic Algorithm As the Optimization Solution Methodsmentioning

confidence: 99%

“…This problem is a mixed-integer non-linear programming problem. It can be solved using a genetic algorithm [11], ant colony optimization [12], particle swarm optimization [13], or other optimization techniques. Solving this problem will be computationally economic since the system resilience function Ψ can be analytically expressed in terms of the target component reliability vector r t , the component-PHM efficiency vector λ t and the target component-redundancy vector m. The proposed RAP incorporates the PHM efficiency in design, where the reliability allocation can be considered as one special case in which PHM efficiencies for all components equal zero.…”

Section: Problem Formulationmentioning

confidence: 99%

“…The aircraft control actuator considered is the EHA (Electro-Hydrostatic Actuator) [20]. In this case study, we aim at designing a highly resilient EHA with optimally allocated reliability, PHM efficiency and redundancy.…”

Section: Aircraft Control Actuator Case Studymentioning

confidence: 99%

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Resilience Allocation for Resilient Engineered System Design

Youn¹,

Hu²,

Wang³

et al. 2011

Journal of Institute of Control, Robotics and Systems

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Most engineered systems are designed with high levels of system redundancies to satisfy required reliability requirements under adverse events, resulting in high systems' LCCs (Life-Cycle Costs). Recent years have seen a surge of interest and tremendous advance in PHM (Prognostics and Health Management) methods that detect, diagnose, and predict the effects of adverse events. The PHM methods enable proactive maintenance decisions, giving rise to adaptive reliability. In this paper, we present a RAP (Resilience Allocation Problem) whose goal is to allocate reliability and PHM efficiency to components in an engineering context. The optimally allocated reliability and PHM efficiency levels serve as the design specifications for the system RBDO (Reliability-Based Design Optimization) and the system PHM design, which can be used to derive the detailed design of components and PHM units. The RAP is demonstrated using a simplified aircraft control actuator design problem resulting in a highly resilient actuator with optimally allocated reliability, PHM efficiency and redundancy for the given parameter settings.

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Section: Genetic Algorithm As the Optimization Solution Methodsmentioning

confidence: 99%

Section: Problem Formulationmentioning

confidence: 99%

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Resilience Allocation for Resilient Engineered System Design

Youn¹,

Hu²,

Wang³

et al. 2011

Journal of Institute of Control, Robotics and Systems

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“…In the local search, a random walk approach is applied for generating a new solution, as shown in formula (5) .…”

Section: Improved Bat Algorithm（iba）mentioning

confidence: 99%

“…A wide variety of meta-heuristic algorithms emerge. At present, the main metaheuristic algorithms for this problem are: genetic algorithm(GA) [2,3,4,5] immune algorithm(IA) [6,29], variable neighborhood search(VNS) [8], particle swarm optimization(PSO) [9,10,11,19], harmony search(HS) [12,13], ant colony optimization(ACO) [14], Tabu Search(TS) [15], imperialist competitive algorithm(ICA) [16]，improved cuckoo search(ICS) algorithm [18] et al Recently, some researchers have proposed hybrid meta-heuristic algorithms by combining with two kinds of meta-heuristic methods to solve the reliability-redundancy allocation problem. Safaei et al [17] proposed particle swarm optimization algorithm based on simulated annealing (APSO).…”

Section: Introductionmentioning

confidence: 99%

Improved Bat Algorithm for Reliability-Redundancy Allocation Problems

Liu¹

2016

IJSIA

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Short communication optimal replacement scheduling in multi-state series-parallel systems

Levitin

Lisnianski

2000

Qual. Reliab. Engng. Int.

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The paper generalizes a replacement schedule optimization problem to multi‐state systems, where the system and its components have a range of performance levels—from perfect functioning to complete failure. The multi‐state system reliability is defined as the ability to satisfy a demand which is represented as a required system performance level. The reliability of system elements is characterized by their lifetime distributions with hazard rates increasing in time and is specified as expected number of failures during different time intervals. The optimal number of element replacements during the study period is defined as that which provides the desired level of the system reliability by minimum sum of maintenance cost and cost of unsupplied demand caused by failures. To evaluate multi‐state system reliability, a universal generating function technique is applied. A genetic algorithm (GA) is used as an optimization technique. Examples of the optimal replacement schedule determination are demonstrated. Copyright © 2000 John Wiley & Sons, Ltd.

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Genetic algorithms for reliability design problems

Cited by 152 publications

References 22 publications

Resilience Allocation for Resilient Engineered System Design

Resilience Allocation for Resilient Engineered System Design

Improved Bat Algorithm for Reliability-Redundancy Allocation Problems

Short communication optimal replacement scheduling in multi-state series-parallel systems

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