A bi-objective simulation-based optimization algorithm for redundancy allocation problem in series-parallel systems

Chambari, Amirhossain; Azimi, Parham; Najafi, Amir Abbas

doi:10.1016/j.eswa.2021.114745

Cited by 34 publications

(7 citation statements)

References 31 publications

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“…Devi and Garg (2020) maximized the reliability of the system in solving an RRAP by employing two heuristic algorithms (HA), viz., Constraint Optimization Genetic Algorithm (COGA) and hybrid genetic-PSO. Chambari et al (2021) introduced a bi-objective simulation optimization algorithm to find a solution for RAP with series-parallel systems. Garg and Sharma (2013) have maximized the reliability of the redundancy allocation non-linear constraint problem of a pharmaceutical plant with the help of a meta-heuristic algorithm for several constraints.…”

Section: Literature Surveymentioning

confidence: 99%

Novel Heuristic Algorithm & its Application for Reliability Optimization

Dahiya,

Vashishth,

Garg

et al. 2023

Int. j. math. eng. manag. sci.

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Heuristic algorithms are practical, easy to implement, and work fast to provide short-term, feasible solutions for any kind of problem within economical budgets as compared to other meta-heuristic algorithms. This paper presents a novel heuristic algorithm named the Dahiya-Garg Heuristic Algorithm (DG-Alg) to find the optimal solution for constrained reliability redundancy allocation optimization problems. The cornerstone of the novel DG-Alg is its novel selection factor, which is a mathematical formula that helps the heuristic algorithm search for optimal subsystems for reliability optimization. A novel formulated selection factor in DG-Alg has increased its effectiveness and efficiency. To analyze the performance of the proposed heuristic algorithm and the other three existing heuristic algorithms, they are applied to a problem taken from a pharmaceutical manufacturing plant named Yaris Pharmaceuticals. During the application of the heuristic algorithms, it was ensured that redundancy allocation was done within stipulated cost constraints. Further, a comparative analysis of the obtained results has been done to judge the performance of the proposed heuristic algorithm. It is deduced that the proposed heuristic algorithm gives optimized and computationally efficient results in comparison to the other existing heuristic algorithms.

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Section: Literature Surveymentioning

confidence: 99%

Novel Heuristic Algorithm & its Application for Reliability Optimization

Dahiya,

Vashishth,

Garg

et al. 2023

Int. j. math. eng. manag. sci.

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show abstract

“…They used NSGA-II with reliability and cost as objective functions. Chambari et al [28] proposed a bi-objective simulation-based optimisation model to redundancy allocation in series-parallel systems with homogeneous components to maximise the system reliability and minimise the cost and using NSGA-II. They considered optimal component types, the redundancy level, and the redundancy strategy (active, cold standby, mixed or K-mixed) with imperfect switching.…”

Section: Redundancy Allocation Of Reliability Systems Design Optimisa...mentioning

confidence: 99%

Multi-Objective Optimum Design and Maintenance of Safety Systems: An In-Depth Comparison Study Including Encoding and Scheduling Aspects with NSGA-II

2021

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Maximising profit is an important target for industries in a competitive world and it is possible to achieve this by improving the system availability. Engineers have employed many techniques to improve systems availability, such as adding redundant devices or scheduling maintenance strategies. However, the idea of using such techniques simultaneously has not received enough attention. The authors of the present paper recently studied the simultaneous optimisation of system design and maintenance strategy in order to achieve both maximum availability and minimum cost: the Non-dominated Sorting Genetic Algorithm II (NSGA-II) was coupled with Discrete Event Simulation in a real encoding environment in order to achieve a set of non-dominated solutions. In this work, that study is extended and a thorough exploration using the above-mentioned Multi-objective Evolutionary Algorithm is developed using an industrial case study, paying attention to the possible impact on solutions as a result of different encodings, parameter configurations and chromosome lengths, which affect the accuracy levels when scheduling preventive maintenance. Non-significant differences were observed in the experimental results, which raises interesting conclusions regarding flexibility in the preventive maintenance strategy.

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“…The former explicitly focused on the RAP while the latter studied a more general JRRAP assuming that repairs are also possible. Recently, these simulation-based methods were further developed by Chambari et al [20] to include mixed and k-mixed strategies for the series-parallel topology. Yeh and Wei [21] presented another simulation optimization approach for allocating resources under reliability concerns and discussed the financial aspects of unreliability of the system.…”

Section: Introductionmentioning

confidence: 99%

A Novel Perspective on Reliable System Design With Erlang Failures and Realistic Constraints for Incomplete Switching Mechanisms

et al. 2023

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This study focuses on effectively designing reliable systems. Such systems are capable of withstanding failure events by applying multiple realistic workarounds. These workarounds include allocating redundancy, component reliability, and backup strategy that are considered concurrently as decision variables. In this novel view, the strategy and reliability of components are determined freely and independently to achieve optimality. The research problem is implemented in a general case to audit the capabilities of the proposed approach in realistic situations. This case deploys an Erlang time-to-failure probability density function together with incomplete switching. With its improved reliability and resource functions, the proposed model challenges the existing presumption regarding the superiority of the coldstandby approach in the mentioned field and provides a realistic trade-off between different redundancy strategies. This practical view reflects on reliability, cost, weight, and volume of the switch, simultaneously. The findings revealed that the proposed joint reliability-redundancy allocation problem, with an added freedom of strategy choice, outperforms the pure cold-standby counterpart. Owing to the NP-hard nature of the problem, a simplified particle swarm optimization algorithm is suggested and utilized as a solution method. The performance of the novel view is assessed using multiple benchmark instances including some typical problems from the literature. Our numerical analysis demonstrates the superiority of this approach with our maximum possible index reaching up to %96 compared to the existing results in the past works. Furthermore, the selected solution algorithm is compared with a differential evolution algorithm. We show that this simplified particle swarm optimization algorithm performs considerably better in all tested scenarios.

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A bi-objective simulation-based optimization algorithm for redundancy allocation problem in series-parallel systems

Cited by 34 publications

References 31 publications

Novel Heuristic Algorithm & its Application for Reliability Optimization

Novel Heuristic Algorithm & its Application for Reliability Optimization

Multi-Objective Optimum Design and Maintenance of Safety Systems: An In-Depth Comparison Study Including Encoding and Scheduling Aspects with NSGA-II

A Novel Perspective on Reliable System Design With Erlang Failures and Realistic Constraints for Incomplete Switching Mechanisms

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