论文标题
带有主动冗余和间隔类型2模糊参数的多目标可靠性 - 可靠性分配问题
A multi-objective reliability-redundancy allocation problem with active redundancy and interval type-2 fuzzy parameters
论文作者
论文摘要
本文考虑了一个串联系统的多目标可靠性分配问题（MORRAP），其中系统的可靠性和系统成本应同时优化，以限制重量，体积和冗余水平。 Precise computation of component reliability is very difficult as the estimation of a single number for the probabilities and performance levels are not always possible, because it is affected by many factors such as inaccuracy and insufficiency of data, manufacturing process, environment in which the system is running, evaluation done by multiple experts, etc. To cope with impreciseness, we model component reliabilities as interval type-2 fuzzy numbers (IT2 FNs), which is more suitable to represent不确定性比平常或1型模糊数字。为了用Interval Type-2模糊参数解决该问题，我们首先应用各种类型的还原和归化技术，并获得相应的脱糊度值。随着系统可靠性的最大化和系统成本的最小化相互冲突，因此，为了获得使用分类参数的Morrap的折衷解决方案，我们采用五种不同的多目标优化方法，然后分析相应的解决方案。该问题在数值上是针对制药植物上现实世界中的Morrap的数字说明，并且通过标准优化求解器Lingo获得了解决方案，该解决方案基于基于基于梯度的优化 - 广义降低梯度（GRG）技术。
This paper considers a multi-objective reliability-redundancy allocation problem (MORRAP) of a series-parallel system, where system reliability and system cost are to be optimized simultaneously subject to limits on weight, volume, and redundancy level. Precise computation of component reliability is very difficult as the estimation of a single number for the probabilities and performance levels are not always possible, because it is affected by many factors such as inaccuracy and insufficiency of data, manufacturing process, environment in which the system is running, evaluation done by multiple experts, etc. To cope with impreciseness, we model component reliabilities as interval type-2 fuzzy numbers (IT2 FNs), which is more suitable to represent uncertainties than usual or type-1 fuzzy numbers. To solve the problem with interval type-2 fuzzy parameters, we first apply various type-reduction and defuzzification techniques, and obtain corresponding defuzzified values. As maximization of system reliability and minimization of system cost are conflicting to each other, so to obtain compromise solution of the MORRAP with defuzzified parameters, we apply five different multi-objective optimization methods, and then corresponding solutions are analyzed. The problem is illustrated numerically for a real-world MORRAP on pharmaceutical plant, and solutions are obtained by standard optimization solver LINGO, which is based on gradient-based optimization - Generalized Reduced Gradient (GRG) technique.
