Solving the redundancy allocation problem of k-out-of-n with non-exponential repairable components using optimization via simulation approach

Azimi, Parham; Hemmati, Marziyeh; Chambari, Amirhossain

doi:10.24200/sci.2017.4134

Cited by 4 publications

(2 citation statements)

References 31 publications

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“…In this regard, we can refer to Simulated Annealing (SA) [8], Genetic Algorithm (GA) [4,[9][10][11][12], Particle Swarm Optimization (PSO) [5,6,[13][14][15][16], Artificial bee colony algorithm [3,17], Artificial immune search [18], Biogeography-based optimization (BBO) [19], fruit fly optimization algorithm [20], Markov decision process [21], Stochastic Fractal Search (SFS) [22], and hybrid algorithms such as SFS-GA [23]. In addition to heuristic and metaheuristic algorithms, simulation-based solution approaches [24] and exact solution methods such as implicit enumeration, branch-and-bound, and dynamic programming have also been used to solve RRAP [23]. GA has been successfully applied to the RRAP [4,9,10].…”

Section: Introductionmentioning

confidence: 99%

Reliability-redundancy allocation Problem of a queueing system considering energy consumption

Sabri-Laghaie¹,

Fathi²

2022

Scientia Iranica

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In Reliability Redundancy Allocation Problem (RRAP), the reliability and redundancy of components in a given system configuration are determined while concerning some problem-specific constraints. RRAP can be applied to various industries. Moreover, queueing systems are among the most common systems in the manufacturing and service industries. Failure in queueing systems can result in unwanted severe damages. Reliability analysis of queueing systems should be undertaken concerning their performance measures. Therefore, an RRAP of a queueing system considering queueing costs is studied in this article. The proposed cost function includes queueing, repair, and energy consumption costs. A memetic algorithm is used to obtain optimal redundancy and failure rates of components and the system's service rate, which affects the energy consumption level. Extensive numerical experiments and sensitivity analyses are performed to present the problem's applicability and the proposed algorithm.

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Section: Introductionmentioning

confidence: 99%

Reliability-redundancy allocation Problem of a queueing system considering energy consumption

Sabri-Laghaie¹,

Fathi²

2022

Scientia Iranica

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“…1,2 . To optimize system reliability, treatment may be employed, including the redundancy allocation problem (RAP), 3–10 the reliability allocation problem, 11–13 reassigning interchangeable components, 14 and the reliability-redundancy allocation problem. 15–17 Due to different structures and premises, each problem differs from the others in the solution.…”

Section: Introductionmentioning

confidence: 99%

Redundancy allocation of heterogeneous components by simulation-based optimization

Chambari

Azimi

Najafi

2021

Proceedings of the Institution of Mechanical Engineers, Part O:

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The present study proposes a novel simulation-based optimization model for a series-parallel redundancy allocation problem (RAP) under heterogeneous components for reliability maximization subjected to system-level constraints through the identification of the optimal redundancy strategy, component type, and subsystem component count. To obtain higher practicality, active, cold-standby, mixed, and K-mixed redundancy strategies are incorporated as the decision variables. In general, as it is difficult to determine a closed-form (excluding active redundancy strategies), it is not possible to analytically assess system reliability. Earlier studies on system reliability optimization applied convenient lower bound approximation. This limits higher reliability levels. In order to tackle this problem, this study adopted simulation sampling to make unbiased efficient reliability estimates. To this end, 4Dscript interpreting programming was utilized to develop a simulation model. As RAP has a combinatorial nature and is a random and NP-hard problem, this study adopted the genetic algorithm (GA) optimization. To validate the model and assess GA efficiency, the numerical findings of some benchmark tests were employed. The proposed approach outperformed earlier approaches in reliability and confidence.

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Redundancy allocation problem with a mixed strategy for a system with k-out-of-n subsystems and time-dependent failure rates based on Weibull distribution: An optimization via simulation approach

et al. 2018

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Reliability improvement for electronics and mechanical systems is vital for engineers in order to design of these systems. For this reason, there are many researches in this scope to help engineers in real world applications. One of the useful methods in reliability optimization is redundancy allocation problem (RAP). In the most previous works, the failure rates of system components are considered to be constant based on negative exponential distribution; whereas, nearly all systems in real world have components with time-dependent failure rates; i.e., the failure rates of system components will be changed time by time. In this paper, we have worked on a RAP for a system under k-out-of-n subsystems with time-dependent components failure rates based on Weibull distribution. Also, the redundancy policy of the proposed system is considered as mixed strategy and the optimization method was based on the simulation technique to obtain reliability function as implicit function. Finally, a branch and bound algorithm has been used to solve the model, exactly.

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Solving the redundancy allocation problem of k-out-of-n with non-exponential repairable components using optimization via simulation approach

Cited by 4 publications

References 31 publications

Reliability-redundancy allocation Problem of a queueing system considering energy consumption

Reliability-redundancy allocation Problem of a queueing system considering energy consumption

Redundancy allocation of heterogeneous components by simulation-based optimization

Redundancy allocation problem with a mixed strategy for a system with k-out-of-n subsystems and time-dependent failure rates based on Weibull distribution: An optimization via simulation approach

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