基于梯度优化的可靠性分配系统求解方法

Zubair Ashraf, Mohammad Shahid, Faisal Ahmad
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引用次数: 2

摘要

提出了一种利用梯度优化器(Gradient-based optimizer, GBO)解决串并联框架可靠性冗余分配问题的方法。在RRAP中,目标是通过同时确定冗余数量和每个子系统的组件可靠性,在考虑不同非线性约束(成本、体积、重量等)的情况下,优化整个系统的可靠性。该算法采用无参数惩罚方法,使算法能够在可行搜索空间和附近可达区域内进行搜索,避免出现不胜任解。为了验证所提出的求解方法的有效性,使用了具有RRAP参数的制药厂数据,并获得了结果。对比研究表明,GBO算法的性能比基于粒子群算法(PSO)的算法高0.044%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Gradient Based Optimization Approach to solve Reliability Allocation System
This paper proposes a solution approach to solve the reliability redundancy allocation problem (RRAP) of a series-parallel framework using a Gradient-based optimizer (GBO). In RRAP, the objective is to optimize the total system's reliability considering different nonlinear constraints (cost, volume, weight, etc.) by simultaneously determining the number of redundancies and the component reliabilities of each subsystem. A parameter-free penalty approach allows the proposed GBO based solution algorithm to benefit the approach to investigate within the feasible search space and the nearby achievable area and prevent incompetent solutions. To prove the effectiveness of the presented solution approach, the data of the pharmaceutical plant with the RRAP parameters are used, and the results are obtained. Comparative study indicates0.044% superior performance of proposed GBO approach to Particle Swarm optimization (PSO) basedapproach.
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