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reliability-redundancy allocation problem with cold-standby redundancy strategy

SIMULATION MODELLING PRACTICE AND THEORY 2014年第0期42卷 107-118页

作者： Ardakan, Mostafa Abouei Hamadani, Ali Zeinal Isfahan Univ Technol Dept Ind & Syst Engn Esfahan *** Iran

This paper considers the mixed-integer non-linear optimization of reliability-redundancy allocation problem (RRAP) to determine simultaneous reliability and redundancy level of components. In the RRAP, it is necessary to create a trade-off between component reliabilities and the number of redundant components with the aim of maximizing system reliability through component reliability choices and component redundancy levels. RRAPs have been generally formulated by considering an active redundancy strategy. A large number of solution methods have been developed to deal with these problems. In this paper, a cold-standby strategy for redundant components is used, for the first time, to model the RRAP;a modified genetic algorithm is developed to solve the proposed non-linear mixed-integer problem;and three famous benchmark problems are used for comparison. The results indicate that the cold-standby strategy exhibits a better performance and yields higher reliability values compared to the previous studies. (C) 2013 Elsevier B.V. All rights reserved.

关键词： reliability optimization reliability-redundancy allocation problem Cold-standby redundancy strategy Genetic algorithm

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reliability-redundancy allocation problem in multi-state flow network: Minimal cut-based approximation scheme

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reliability ENGINEERING & SYSTEM SAFETY 2022年 225卷 1页

作者： Zhang, Hanxiao Sun, Muxia Li, Yan-Fu Tsinghua Univ Dept Ind Engn Beijing 100084 Peoples R China

reliability-redundancy allocation problem (RRAP), a challenging reliability optimization problem, aims to optimize the redundancy level and the component reliability simultaneously for each stage (i.e. subsystem) of the system. The RRAP was mainly studied under binary-state setting on different redundancy strategies, methodologies, and multi-objective formulations. However, the methods are all meta-heuristic algorithms, and no studies focused on RRAP in multi-state flow network (MFN) systems. In this paper, we study the RRAP in MFN considering the minimization of cost or the maximization of reliability under resource constraints. The MFN RRAP is a mixed-integer non-linear programming problem, which is NP-hard. We propose a minimal cut-based approximation scheme to transform it into an integer programming problem. The feasibility guarantee is analyzed to ensure that this approximation scheme can generate a feasible solution with a high probability. The posterior check is conducted to reduce the conservative theoretical sample size empirically. The numerical experiments on MFNs illustrate the tradeoff performance between the accuracy of solutions and the computational complexity, and the outperformance of our proposed method compared to a meta-heuristic algorithm.

关键词： reliability reliability-redundancy allocation problem Multi-state flow network Approximation Integer problem

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Water cycle algorithm for solving the reliability-redundancy allocation problem with a choice of redundancy strategies

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COMMUNICATIONS IN STATISTICS-THEORY AND METHODS 2020年第11期49卷 2728-2748页

作者： Mahdavi-Nasab, Narges Ardakan, Mostafa Abouei Mohammadi, Mohammad Kharazmi Univ Dept Ind Engn Fac Engn Tehran Iran

This paper proposes a new mathematical model for the reliability-redundancy allocation problem (RRAP) with a choice of redundancy strategies. To maximize the reliability of a system, this model chooses the best redundancy strategy from among both active and standby ones for each subsystem. For those with a standby strategy, a continuous time Markov chain model is used to calculate the exact reliability values. In order to solve the proposed mixed-integer non-linear programing model, a powerful evolutionary algorithm, called water cycle algorithm (WCA), is developed and implemented on three famous benchmark problems. Finally, the results of different benchmark problems are compared with those previously reported to show the superiority of the proposed model and the efficiency of WCA.

关键词： reliability optimization reliability-redundancy allocation problem choice of strategy continuous time Markov chain model water cycle algorithm

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Bi-objective optimization of the reliability-redundancy allocation problem for series-parallel system

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JOURNAL OF MANUFACTURING SYSTEMS 2014年第3期33卷 335-347页

作者： Garg, Harish Rani, Monica Sharma, S. P. Vishwakarma, Yashi Thapar Univ Sch Math & Comp Applicat Patiala 147004 Punjab India Indian Inst Technol Dept Math Roorkee 247667 Uttarakhand India

The main objective of this paper is to solve the bi-objective reliability redundancy allocation problem for series-parallel system where reliability of the system and the corresponding designing cost are considered as two different objectives. In their formulation, reliability of each component is considered as a triangular fuzzy number. In order to solve the problem, developed fuzzy model is converted to a crisp model by using expected values of fuzzy numbers and taking into account the preference of decision maker regarding cost and reliability goals. Finally the obtained crisp optimization problem has been solved with particle swarm optimization (PSO) and compared their results with genetic algorithm (GA). Examples are shown to illustrate the method. Finally statistical simulation has been performed for supremacy the approach. (C) 2014 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.

关键词： Multi-objective optimization PSO reliability-redundancy allocation problem Membership functions

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A novel evolutionary solution approach for many-objective reliability-redundancy allocation problem based on objective prioritization and constraint optimization

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reliability ENGINEERING & SYSTEM SAFETY 2024年 244卷

作者： Nath, Rahul Muhuri, Pranab K. Univ Bergen Dept Informat Thormohlens Gate 55 N-5008 Bergen Norway South Asian Univ Dept Comp Sci Rajpur Rd New Delhi 110068 India

The reliability redundancy allocation problem (RRAP) has been mostly solved either as a single or as a multiobjective optimization problem. However, this problem also has numerous important constraints which play prominent roles in meeting the objectives. This paper proposes a novel formulation named 'prioritized many reliability redundancy allocation problems (PrMaORRAP)' that optimizes all the problem objectives concurrently, and also preserves the priority among them. Then, we propose a hybrid method which utilizes the features of many-objective optimization as well as priority relations between different objectives. Here, we divide the procedure into two modules: one is the main priority or the leader which will stay at the top level;underneath the first lie the second part in which rest of the objectives are optimized. The solution approach embeds the optimization structure within the evolutionary process making a prioritized many-objective evolutionary algorithms. We formulate various structures such as series, series-parallel, complex bridge and overspeed gas turbine system of RRAP as many-objective optimization problems, and provide detailed experimental demonstration on how our proposed model works for all these structures. We compare the results given by the proposed approach with the results of other approaches available in the literature and establish the superiority of our proposed solution approach.

关键词： Many-objective optimization reliability-redundancy allocation problem (RRAP) Evolutionary algorithm Evolutionary optimization Objective prioritization

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An improved particle swarm optimization algorithm for reliability-redundancy allocation problem with mixed redundancy strategy and tor heterogeneous components

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reliability ENGINEERING & SYSTEM SAFETY 2019年 181卷 62-74页

作者： Ouyang, Zhiyuan Liu, Yu Ruan, Sheng-Jia Jiang, Tao Univ Elect Sci & Technol China Sch Mech & Elect Engn Chengdu 611731 Sichuan Peoples R China Univ Elect Sci & Technol China Ctr Syst Reliabil & Safety 2006 Xiyuan Ave Chengdu 611731 Sichuan Peoples R China

The reliability-redundancy allocation problem (RRAP) has been intensively studied to identify the optimal system design under several constraints, so as to maximize the system reliability as much as possible. Recently, the mixed redundancy strategy where both active redundant components and cold standby components can be simultaneously used by a subsystem has been introduced into the RRAP, leading to a more superior result than that of a subsystem with either active redundancy strategy or cold standby strategy. Nevertheless, in the existing studies, all the components deployed in a subsystem have to be homogeneous even if the mixed redundancy strategy is chosen. The strong premise is released in this paper by introducing heterogeneous components into the RRAP. The resulting optimization problem is resolved by proposing an improved particle swarm optimization (PSO) algorithm with stochastic perturbation nature. The efficiency of the proposed algorithm has been demonstrated by conducting a set of comparative studies on three benchmark problems. As observed in our study, the design flexibility introduced by our method can always yield a greater system reliability than that of the state-of-the-art methods. Most importantly, we also reveal that the switching reliability has significant influence on the optimal system configuration.

关键词： reliability-redundancy allocation problem Mixed redundancy strategy Heterogeneous components Improved particle swarm optimization algorithm

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A new model for the reliability-redundancy allocation problem with the mixed redundancy strategy

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JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION 2022年第14期92卷 2956-2979页

作者： Mahdavi-Nasab, Narges Ardakan, Mostafa Abouei Peiravi, Abdossaber Kharazmi Univ Fac Engn Ind Engn Tehran 15614 Iran

In this paper, the reliability-redundancy allocation problem with the mixed redundancy strategy is revisited to develop a new model that can be beneficially exploited to estimate exact reliability values. The model is capable of not only optimally calculating reliability values in a very short time but also choosing the best strategy for each subsystem from among active, standby, and mixed strategies. In previous studies, reliability calculation for the mixed strategy had been accomplished using a lower bound formulation that was sophisticated, time-consuming, and approximate. The proposed model is developed based on a continuous-time Markov chain model. It is applied to three famous benchmark tests that are subsequently solved using a powerful evolutionary algorithm called the water cycle algorithm. Computational results confirm the robustness and superiority of this new model over previous ones in calculating reliability. Besides, the proposed algorithm outperforms the previous ones in finding good results.

关键词： reliability-redundancy allocation problem mixed redundancy strategy exact formulation water cycle algorithm Markov model

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FUZZY MULTI-OBJECTIVE reliability-redundancy allocation problem

FUZZY MULTI-OBJECTIVE RELIABILITY-REDUNDANCY ALLOCATION PROB...

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IEEE International Conference on Fuzzy Systems

作者： Ashraf, Zubair Muhuri, Pranab K. Lohani, Q. M. Danish Nath, Rahul South Asian Univ Fac Math & Comp Sci New Delhi 110021 India

ISBN: (纸本)9781479920723

reliability is the measure of the result of the quality of the system over a long run. The reliability-redundancy allocation problem (RRAP) aims to ensure high systems reliability in the presence of optimally redundant systems components. This is one of the most important design considerations for the systems designers. Several researchers have addressed this important issue during last few decades. However, due to the embedded uncertainty in the parameters of the system components, reliability as well as the costs of the whole system fits very well to be modeled as fuzzy quantity. We therefore modeled this problem as a fuzzy multi-objective optimization problem (MORRAP) that is addressed using the popular multi-objective evolutionary algorithm, NSGA-II (non-dominated sorting genetic algorithm-II). We have considered the based MORRAP with fuzzy type-2 uncertainty. As far as we know, no research has been reported where MORRAP was considered under type-2 fuzzy uncertainty. A typical numerical example is included and results are compared showing that our approach outperforms other recently reported results.

关键词： reliability redundancy reliability-redundancy allocation problem NSGA-II Fuzzy reliability Fuzzy Cost

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RRAP-CM: A new reliability-redundancy allocation problem with heterogeneous components

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reliability ENGINEERING & SYSTEM SAFETY 2019年 191卷 106563-000页

作者： Dobani, Ehsan Ramezani Ardakan, Mostafa Abouei Davari-Ardakani, Hamed Juybari, Mohammad N. Kharazmi Univ Fac Engn Dept Ind Engn Tehran Iran

In this paper, a new version of the reliability-redundancy allocation problem (RRAP) is introduced. In RRAPs, the reliability of the components used in a subsystem is considered as a decision variable and it is also assumed that all the redundant components in each subsystem have the same reliability value. The latter assumption is a restricting and unrealistic one. In this paper, the RRAP is for the first time investigated with the assumption of component mixing, which changes the traditional RRAP model to a more complicated heterogeneous one. A new mathematical model is developed and implemented on different benchmark test problems. Moreover, a powerful meta-heuristic algorithm, called stochastic fractal search (SFS), is used to solve the new mixed integer non-liner programing (MINLP) models. The advantages of the new RRAP model are demonstrated by comparing the results with those reported in the literature. Results reveal that in all the test problems, better structures with higher reliability values are obtained. The improvement values are also compared with improvements achieved in recent studies.

关键词： reliability-redundancy allocation problem Heterogeneous components Hybrid algorithm Stochastic fractal search (SFS) Genetic algorithm (GA)

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Evolutionary Optimization based Solution approaches for Many Objective reliability-redundancy allocation problem

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reliability ENGINEERING & SYSTEM SAFETY 2022年第0期220卷 108190-108190页

作者： Nath, Rahul Muhuri, Pranab K. South Asian Univ Dept Comp Sci New Delhi 110021 India

Recently, a number of evolutionary optimization approaches were proposed to solve the many objective problems. The reliability redundancy allocation problem (RRAP), which usually has four different objectives, namely, maximization of system reliability, minimizations of cost, weight and volume, are however solved mainly as a multi-objective problem considering only two or three objectives. Therefore, this paper reports a novel study of the RRAP as a many objective optimization problem. Here, we formulate the many objective RRAP (MaORRAP) with various structures such as series-parallel systems, overspeed gas turbine system, and large-scale system. For the formulated MaORRAP, we then provide the details of a novel solution procedure based on the non-dominated sorting genetic algorithm-III (NSGA-III), a well-discussed many objective evolutionary optimization algorithm. We also solve MaORRAP using three other popular evolutionary approaches, viz. non-dominated sorting genetic algorithm-II (NSGA-II), multi-objective evolutionary algorithm based on decomposition (MOEA/D) and strength Pareto evolutionary archive 2 (SPEA2) algorithm. Accordingly, we present all the results in a competitive fashion to have a thorough comparative assessment of the performances of the considered approaches and show that, in most of the cases, NSGA-III based solutions are superior to others.

关键词： Evolutionary optimization reliability-redundancy allocation problem many objective reliability-redundancy allocation problem NSGA-III NSGA-II SPEA2 MOEA/D

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