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Ali Zeinal Hamadani - One of the best experts on this subject based on the ideXlab platform.

  • reliability optimization of series parallel systems with mixed Redundancy strategy in subsystems
    Reliability Engineering & System Safety, 2014
    Co-Authors: Mostafa Abouei Ardakan, Ali Zeinal Hamadani
    Abstract:

    Traditionally in Redundancy allocation problem (RAP), it is assumed that the redundant components are used based on a predefined active or standby strategies. Recently, some studies consider the situation that both active and standby strategies can be used in a specific system. However, these researches assume that the Redundancy strategy for each subsystem can be either active or standby and determine the best strategy for these subsystems by using a proper mathematical model. As an extension to this assumption, a novel strategy, that is a combination of traditional active and standby strategies, is introduced. The new strategy is called mixed strategy which uses both active and cold-standby strategies in one subsystem simultaneously. Therefore, the problem is to determine the component type, Redundancy Level, number of active and cold-standby units for each subsystem in order to maximize the system reliability. To have a more practical model, the problem is formulated with imperfect switching of cold-standby redundant components and k-Erlang time-to-failure (TTF) distribution. As the optimization of RAP belongs to NP-hard class of problems, a genetic algorithm (GA) is developed. The new strategy and proposed GA are implemented on a well-known test problem in the literature which leads to interesting results.

  • reliability Redundancy allocation problem with cold standby Redundancy strategy
    Simulation Modelling Practice and Theory, 2014
    Co-Authors: Mostafa Abouei Ardakan, Ali Zeinal Hamadani
    Abstract:

    Abstract 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.

  • Reliability–Redundancy allocation problem with cold-standby Redundancy strategy
    Simulation Modelling Practice and Theory, 2014
    Co-Authors: Mostafa Abouei Ardakan, Ali Zeinal Hamadani
    Abstract:

    Abstract 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.

Mostafa Abouei Ardakan - One of the best experts on this subject based on the ideXlab platform.

  • reliability optimization of series parallel systems with mixed Redundancy strategy in subsystems
    Reliability Engineering & System Safety, 2014
    Co-Authors: Mostafa Abouei Ardakan, Ali Zeinal Hamadani
    Abstract:

    Traditionally in Redundancy allocation problem (RAP), it is assumed that the redundant components are used based on a predefined active or standby strategies. Recently, some studies consider the situation that both active and standby strategies can be used in a specific system. However, these researches assume that the Redundancy strategy for each subsystem can be either active or standby and determine the best strategy for these subsystems by using a proper mathematical model. As an extension to this assumption, a novel strategy, that is a combination of traditional active and standby strategies, is introduced. The new strategy is called mixed strategy which uses both active and cold-standby strategies in one subsystem simultaneously. Therefore, the problem is to determine the component type, Redundancy Level, number of active and cold-standby units for each subsystem in order to maximize the system reliability. To have a more practical model, the problem is formulated with imperfect switching of cold-standby redundant components and k-Erlang time-to-failure (TTF) distribution. As the optimization of RAP belongs to NP-hard class of problems, a genetic algorithm (GA) is developed. The new strategy and proposed GA are implemented on a well-known test problem in the literature which leads to interesting results.

  • reliability Redundancy allocation problem with cold standby Redundancy strategy
    Simulation Modelling Practice and Theory, 2014
    Co-Authors: Mostafa Abouei Ardakan, Ali Zeinal Hamadani
    Abstract:

    Abstract 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.

  • Reliability–Redundancy allocation problem with cold-standby Redundancy strategy
    Simulation Modelling Practice and Theory, 2014
    Co-Authors: Mostafa Abouei Ardakan, Ali Zeinal Hamadani
    Abstract:

    Abstract 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.

Ming J Zuo - One of the best experts on this subject based on the ideXlab platform.

  • a joint reliability Redundancy optimization approach for multi state series parallel systems
    Reliability Engineering & System Safety, 2009
    Co-Authors: Zhigang Tian, Gregory Levitin, Ming J Zuo
    Abstract:

    Abstract In this paper, we present a practical approach for the joint reliability–Redundancy optimization of multi-state series–parallel systems. In addition to determining the optimal Redundancy Level for each parallel subsystem, this approach also aims at finding the optimal values for the variables that affect the component state distributions in each subsystem. The key point is that technical and organizational actions can affect the state transition rates of a multi-state component, and thus affect the state distribution of the component and the availability of the system. Taking this into consideration, we present an approach for determining the optimal versions and numbers of components and the optimal set of technical and organizational actions for each subsystem of a multi-state series–parallel system, so as to minimize the system cost while satisfying the system availability constraint. The approach might be considered to be the multi-state version of the joint system reliability–Redundancy optimization methods.

Gregory Levitin - One of the best experts on this subject based on the ideXlab platform.

  • Redundancy optimization for series-parallel phased mission systems exposed to random shocks
    Reliability Engineering & System Safety, 2017
    Co-Authors: Gregory Levitin, Maxim Finkelstein, Yuanshun Dai
    Abstract:

    Abstract Systems performing consecutive non-overlapping mission phases in a random environment are considered. Each phase is performed by a specific 1-out-of- n subsystem consisting of statistically identical parallel elements with the same functionality. The environment is modeled by the Poisson process of shocks commonly affecting all elements, by increasing their failure rate. A method for evaluating the mission success probability for arbitrary Redundancy Level in each subsystem is presented. The constrained Redundancy allocation problem is formulated and solved. Illustrative examples are presented.

  • a joint reliability Redundancy optimization approach for multi state series parallel systems
    Reliability Engineering & System Safety, 2009
    Co-Authors: Zhigang Tian, Gregory Levitin, Ming J Zuo
    Abstract:

    Abstract In this paper, we present a practical approach for the joint reliability–Redundancy optimization of multi-state series–parallel systems. In addition to determining the optimal Redundancy Level for each parallel subsystem, this approach also aims at finding the optimal values for the variables that affect the component state distributions in each subsystem. The key point is that technical and organizational actions can affect the state transition rates of a multi-state component, and thus affect the state distribution of the component and the availability of the system. Taking this into consideration, we present an approach for determining the optimal versions and numbers of components and the optimal set of technical and organizational actions for each subsystem of a multi-state series–parallel system, so as to minimize the system cost while satisfying the system availability constraint. The approach might be considered to be the multi-state version of the joint system reliability–Redundancy optimization methods.

Zhigang Tian - One of the best experts on this subject based on the ideXlab platform.

  • a joint reliability Redundancy optimization approach for multi state series parallel systems
    Reliability Engineering & System Safety, 2009
    Co-Authors: Zhigang Tian, Gregory Levitin, Ming J Zuo
    Abstract:

    Abstract In this paper, we present a practical approach for the joint reliability–Redundancy optimization of multi-state series–parallel systems. In addition to determining the optimal Redundancy Level for each parallel subsystem, this approach also aims at finding the optimal values for the variables that affect the component state distributions in each subsystem. The key point is that technical and organizational actions can affect the state transition rates of a multi-state component, and thus affect the state distribution of the component and the availability of the system. Taking this into consideration, we present an approach for determining the optimal versions and numbers of components and the optimal set of technical and organizational actions for each subsystem of a multi-state series–parallel system, so as to minimize the system cost while satisfying the system availability constraint. The approach might be considered to be the multi-state version of the joint system reliability–Redundancy optimization methods.