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Birnbaum importance-based simulated annealing algorithm for solving the component assignment problem of linear connected-(r, s)-out-of-(m, n):F lattice systems

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INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT 2024年第4期15卷 1407-1414页

作者： Nakamura, Taishin Homma, Isshin Yamamoto, Hisashi Tokai Univ Dept Informat Engn 1-4-1 Kitakaname Hiratsuka Kanagawa 2591292 Japan Tokyo Metropolitan Univ Dept Syst Design 6-6 Asahigaoka Hino Tokyo 1910065 Japan

The component assignment problem (CAP) is one of the most important problems in reliability engineering. This paper proposes a Birnbaum importance-based simulated annealing (SA) algorithm for the CAP of linear connected-(r, s)-out-of-(m, n):F lattice systems. Here, the CAP is assigning the components to maximize system reliability, and Birnbaum importance is a measure of the importance of a component assigned at a certain position in the CAP. If the number of components is small, this problem can be solved within an acceptable time by enumerating all solution candidates. However, it is difficult to solve the problem by using this approach with large numbers of components, because the required computational time increases rapidly with the number of components. Based on these factors, we propose an algorithm to solve the CAP of large-sized linear connected-(r, s)-out-of-(m, n):F lattice systems within an acceptable time. We performed numerical experiments to evaluate the effectiveness of combining Birnbaum importance and SA because the proposed algorithm could aid in designing reliable systems.

关键词： Linear connected-(r.s)-out-of-(m.n):F lattice system component assignment problem Simulated annealing Birnbaum importance

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Proposal of an Algorithm for Solving the component assignment problem of an Adjacent Triangle-(m, n):F Triangular Lattice System 22nd

Proposal of an Algorithm for Solving the Component Assignmen...

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22nd International Conference on Computer Information Systems and Industrial Management (CISIM)

作者： Nakamura, Taishin Tokai Univ Sch Informat Sci & Technol 4-1-1 Kitakaname Hiratsuka Kanagawa 2591292 Japan

ISBN: (纸本)9783031428227;9783031428234

In this article, we investigate the component assignment problem, which involves determining the optimal component arrangement for maximizing system reliability, given individual component reliabilities. Establishing the optimal arrangement is crucial for the cost-effective design of dependable systems. We focus on the adjacent triangle(m, n):F triangular lattice system, characterized by mn components arranged in a triangular grid. The system fails when three neighboring components located at the vertices of a triangle fail simultaneously. Applications of this system extend to surveillance camera systems, sprinkler systems, and sensing systems. To date, no algorithm has been reported for finding the optimal arrangement of the adjacent triangle(m, n):F triangular lattice system. Therefore, this paper aims to develop an algorithm using the branch-and-bound method to determine the optimal arrangement of the adjacent triangle-(m, n):F triangular lattice system. To efficiently acquire the optimal arrangement, we derived three pruning conditions and devised an optimal arrangement search algorithm incorporating them. Computational experiments revealed that all pruning conditions decreased computation time. Specifically, the pruning condition based on necessary conditions reduced computation time on average by approximately 1/9, as demonstrated experimentally. The solutions provided by the proposed algorithm ensure optimality, enabling the assessment of approximation methods, such as metaheuristics.

关键词： adjacent triangle-(m, n):F triangular lattice system component assignment problem exact method branch-and-bound

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Algorithm for Solving the component assignment problem in a Multistate Sliding Window System

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INTERNATIONAL JOURNAL OF RELIABILITY QUALITY AND SAFETY ENGINEERING 2021年第6期28卷

作者： Nakamura, Taishin Tokai Univ Sch Informat Sci & Technol Hiratsuka Kanagawa Japan

The multistate sliding window system (SWS) comprises n multistate components arranged in a line;each group of r consecutive multistate components is considered as a window. If the total performance rate in a window does not meet the predetermined demand W, then that window is regarded as a failure. The SWS fails if and only if there exists at least one failed window. Several researchers have considered the component assignment problem for the SWS with the aim of finding an appropriate component arrangement that maximizes system reliability. Such an arrangement is called the optimal arrangement. Although several metaheuristic and heuristic algorithms have been proposed, an exact algorithm for solving the component assignment problem of the SWS has not been developed thus far. Therefore, in this study, a branch-and-boundbased algorithm is developed to determine the optimal arrangement of the SWS efficiently. Furthermore, a recursive method is proposed to compute the system reliability. Combining the branch-and-bound-based algorithm with the recursive method enables reduction of the complexity of the reliability computations for determining the optimal arrangement. To investigate the efficiency of the branch-and- bound- based algorithm, numerical experiments were conducted;it was observed that the parameters n and r have the maximum effect on computation time, whereas parameter W has minimal effect. The proposed algorithm is useful for improving the reliability of a practical system that can be expressed as an SWS. In addition, the optimal arrangements can be used to measure the heuristic and metaheuristic performances because they guarantee global optimality.

关键词： Multistate sliding window system component assignment problem optimal arrangement system reliability

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Joint optimization of multi-type component procurement and assignment problems with budget constraint

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART O-JOURNAL OF RISK AND RELIABILITY 2025年

作者： Qiu, Siqi Tu, Danhong Ming, Xinguo Shanghai Jiao Tong Univ SJTU Paris Elite Inst Technol Shanghai Peoples R China China Shipbuilding Power Engn Inst Co Ltd Shanghai Peoples R China Shanghai Jiao Tong Univ Sch Mech Engn 800 Dongchuan Rd Shanghai 200240 Peoples R China

There are usually multiple types of products with similar functions available on the market, and the price of a product depends on its functionality and reliability. For some industrial systems whose components are functionally exchangeable, different component procurement plans and assignment plans lead to different system reliability and procurement cost. The objective of multi-type component assignment problem (MCAP) is to search the optimal assignment of multiple types of components to the positions of a system for maximizing the system reliability. However, in the existing studies on MCAPs, a particular position can be assigned at most two types of components and the budget constraint has not been taken into consideration. This work studies a new type of MCAPs in which a particular position can be assigned multiple types of components, develops the mathematical model of the MCAP with budget constraint, and proposes a Birnbaum importance (BI)-based two-stage heuristic to solve the budget-constrained MCAP. The proposed method is applied to a real-world fuel service system of marine engines to show its feasibility and practicability.

关键词： component assignment problem heuristic algorithm Birnbaum importance reliability optimization budget constraint

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An extended Birnbaum importance-based two-stage heuristic for component assignment problems under uncertainty

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RELIABILITY ENGINEERING & SYSTEM SAFETY 2020年 204卷

作者： Qiu, Siqi Ming, Xinguo Shanghai Jiao Tong Univ Sch Mech Engn Shanghai 200240 Peoples R China Shanghai Key Lab Adv Mfg Environm Shanghai 200240 Peoples R China

The component assignment problem (CAP) is to find the optimal assignment of n components to n positions in a system that maximizes the system reliability. Due to the insufficiency and the inaccuracy of related data and system complexities, there are different types of uncertainties in real-world engineering system analysis. This paper proposes an extended Birnbaum importance (BI)-based two-stage (EBITS) heuristic using evidential network and interval-valued BI measures for solving CAPs under parametric and model uncertainties. The parametric uncertainty is the uncertainty about component reliabilities and the model uncertainty is the uncertainty about the system structure. The proposed method is applied to find the optimal assignment of valves in a ship's fuel service system.

关键词： component assignment problem Uncertainty analysis Evidential network Birnbaum importance

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A Birnbaum-importance based genetic local search algorithm for component assignment problems

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ANNALS OF OPERATIONS RESEARCH 2014年第1期212卷 185-200页

作者： Yao, Qingzhu Zhu, Xiaoyan Kuo, Way Univ Tennessee Dept Ind & Syst Engn Knoxville TN 37996 USA Revenue Analyt Inc Atlanta GA 30339 USA City Univ Hong Kong Kowloon Hong Kong Peoples R China

This paper considers the component assignment problem (CAP) of finding the optimal assignment of n available components to n positions in a system such that the system reliability is maximized. To solve the CAP, an important type of problems in reliability, we propose a Birnbaum-importance based genetic local search (BIGLS) algorithm in which a local search using the Birnbaum importance is embedded into the genetic algorithm. This paper presents comprehensive numerical tests to compare the performance of the BIGLS with a general genetic algorithm and a Birnbaum-importance based two-stage heuristic. The testing results show that the BIGLS is robust (with respect to its random operations) and effective, and outperforms two benchmark methods in terms of solution quality. It demonstrates the effectiveness of embedding the Birnbaum importance in the local search under the genetic evolutionary mechanism.

关键词： Genetic algorithm Reliability Local search component assignment problem Birnbaum importance

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Birnbaum Importance in Solving component assignment problems

Birnbaum Importance in Solving Component Assignment Problems

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Annual Reliability and Maintainability Symposium (RAMS)

作者： Zhu, Xiaoyan Yao, Qingzhu Kuo, Way Univ Tennessee Dept Ind & Informat Engn 307 E Stadium Hall Knoxville TN 37919 USA City Univ Hong Kong Kowloon Hong Kong Peoples R China

ISBN: (纸本)9781424451036

As an important type of reliability optimization problems, the component assignment problem (CAP) is to find the optimal arrangement of n available components to n positions of a system such that the resulting system reliability is maximized. The CAP is a combinatorial problem in nature and needs effective solution methods. The importance measures of components, e.g., the Birnbaum importance (BI), evaluate the relative strength of a component to system reliability, and can be used in aid to tackle the CAP. This paper studies the competence of the BI in solving the CAP. It proposes some BI-based heuristic methods for the CAP, and evaluates and compares the BI-based heuristics, including the new ones and the existing ones, through comprehensive numerical experiments. It is demonstrated that the heuristics using the BI can solve the CAP satisfactorily and the new heuristics are superior to the existing ones under some situ ations. Through the analysis to the computational results, this paper suggests a two-phase procedure for solving the CAP, and each phase uses different BI-based heuristics. © 2011 IEEE.

关键词： Birnbaum importance component assignment problem Heuristics

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Ant Colony Optimization for component assignment problems in Circular Consecutive-k-out-of-n Systems

Ant Colony Optimization for Component Assignment Problems in...

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IEEE International Conference on Industrial Engineering and Engineering Management (IEEE IEEM)

作者： Cai, Z. Q. Wang, W. Zhang, S. Jiang, Z. Y. Northwestern Polytech Univ Sch Mech Engn Xian Shaanxi Peoples R China

ISBN: (纸本)9781538609484

The Circular Consecutive-k-out-of-n (Cir/Con/k/n) system consists of n components arranged in a circular sequence and each component has different reliability. The purpose of optimization is to obtain an optimal assignment which can make the Cir/Con/k/n system most reliable. As the number of components n increases, the computation time for the optimization of Cir/Con/k/n system will increase considerably. In this paper, we propose applying the Ant Colony Optimization (ACO) algorithm to obtain quasi optimal assignments for such problems. First of all, we describe the basic principles and the operation procedures of ACO through pseudo code. After that, a large number of simulation experiments on different types of systems and components are carried out to verify the effectiveness of the ACO. The results of simulation experiments demonstrate the advantage of ACO in the optimization of Cir/Con/k/n system.

关键词： Cir/Con/k/n system Optimization Ant colony optimization component assignment problem

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Heuristics for component assignment problems based on the Birnbaum importance

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IIE TRANSACTIONS 2011年第9期43卷 633-646页

作者： Yao, Qingzhu Zhu, Xiaoyan Kuo, Way Univ Tennessee Dept Ind & Informat Engn Knoxville TN 37919 USA City Univ Hong Kong Kowloon Hong Kong Peoples R China

This article considers the component assignment problem (CAP), which concerns the problem of finding the optimal arrangement of n available components in the n positions of a system so that the system reliability is maximized. The Birnbaum Importance (BI) is a well-known measure that evaluates the relative contributions of components to system reliability. The ordering of BI values of components is a good indicator for the solution of the CAP and has been used to design heuristics for the CAP. This article proposes five new BI-based heuristics and presents their corresponding properties. Based on the numerical testing of the BI-based heuristics, a two-stage approach is proposed to solve the CAP with each stage using different BI-based heuristics. Comprehensive numerical experiments involving both small and large systems are used to evaluate the two-stage approach and to benchmark it against the GAMS/CoinBonmin solver and a randomization method. The numerical results show that the two-stage approach is much more efficient and is able to generate solutions of higher quality than the GAMS/CoinBonmin solver and the randomization method.

关键词： component assignment problem Birnbaum importance heuristics invariant optimal design statistical analysis

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A Birnbaum importance-based two-stage approach for two-type component assignment problems

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RELIABILITY ENGINEERING & SYSTEM SAFETY 2022年 218卷

作者： Qiu, Siqi Ming, Xinguo Sallak, Mohamed Lu, Jialiang Shanghai Jiao Tong Univ SJTU Paris Elite Inst Technol Shanghai 200240 Peoples R China Shanghai Jiao Tong Univ Sch Mech Engn Shanghai 200240 Peoples R China Univ Technol Compiegne Sorbonnes Univ Lab Heudiasyc UMR CNRS 7253 F-60203 Compiegne France

The multi-type component assignment problem (MCAP) aims to find the optimal assignment of multiple types of components to positions in a system that maximizes the system reliability. In MCAPs, a component of a particular type can only be assigned to a position of the same type in the system. The existing works on MCAPs assumed that a particular position can only be assigned a particular type of components. However, this assumption is not necessarily true in some real problems. This paper extends the existing works on MCAPs, and studies the two-type component assignment problem (TCAP) which is a special kind of the MCAP. In the studied TCAP, there are two types of components, and a particular position can be assigned at least one type of components. A Birnbaum importance-based two-stage approach is proposed to solve the TCAP. The proposed approach is illustrated by analytical examples, and numerical experiments are conducted to evaluate its performance. A real-world use case is given to show the feasibility and applicability of the proposed approach. The originality of this work lies in the proposition of a new mathematical model of the TCAP and a two-stage approach to solve such a problem.

关键词： component assignment problem Birnbaum importance Local search heuristic Reliability

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