Sharifi Mani, Moghaddam Tahmine Ashoori, Shahriari Mohammadreza
Faculty of Industrial & Mechanical Engineering, Islamic Azad University, Qazvin Branch, Qazvin, Iran.
Faculty of Industrial Engineering, Islamic Azad University, South Tehran Branch, Tehran, Iran.
Heliyon. 2019 Dec 13;5(12):e02346. doi: 10.1016/j.heliyon.2019.e02346. eCollection 2019 Dec.
Redundancy Allocation Problem (RAP) is one of the most practical problems in the reliability area. Many assumptions have been added to RAP in recent years. The aim was to better represent real-world problems with RAP. One of these assumptions is considering weighted-k-out-of-n sub-systems. This method has been used to model various systems like power and hydro transitions systems. In this paper, we present a new multi-objective RAP (MORAP) model for optimizing the reliability and cost of the weighted-k-out-of-n parallel systems. In our model, the sub-systems are considered as weighted-k-out-of-n. Also, we use the universal generating function and adapt this technique to obtain an exact formula to calculate each sub-system reliability. Since RAP belongs to NP-hard class of problems, we decided to employ the non-dominated sorting genetic algorithm and non-dominated ranked genetic algorithm. Several criteria were used to compare the result of these two algorithms.
冗余分配问题（RAP）是可靠性领域中最实际的问题之一。近年来，许多假设被添加到RAP中。目的是用RAP更好地表示现实世界中的问题。其中一个假设是考虑加权n中取k子系统。这种方法已被用于对各种系统进行建模，如电力和水力转换系统。在本文中，我们提出了一种新的多目标RAP（MORAP）模型，用于优化加权n中取k并行系统的可靠性和成本。在我们的模型中，子系统被视为加权n中取k。此外，我们使用通用生成函数并采用该技术来获得计算每个子系统可靠性的精确公式。由于RAP属于NP难问题类别，我们决定采用非支配排序遗传算法和非支配排名遗传算法。使用了几个标准来比较这两种算法的结果。
