خلاصة:
One of the most practical methods for improving system reliability is making a tradeoff between components reliability and redundancy levels, which is known as reliability-redundancy allocation problem (RRAP). The RRAP aims to maximize the overall system reliability by creating a balance between the component reliabilities and the number of redundant components in each subsystem. In the RRAP, the redundant components are performed in a predetermined order under a redundancy strategy. In this paper, a cold standby redundancy strategy is considered for the redundant components. Besides, a penalty guided water cycle algorithm is adjusted for solving the problem. The proposed algorithm is implemented on two famous benchmark problems to evaluate the performance of the proposed approach. The obtained numerical results reveal the superiority of the proposed solution method over all previous studies
ملخص الجهاز:
com An Adjusted Water Cycle Algorithm for Solving Reliability-redundancy Allocation Problems with Cold-standby Components Mohammad N.
Juybari a, Mostafa Abouei Ardakan*, a, Hamed Davari-Ardakani a a Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran Abstract One of the most practical methods for improving system reliability is making a tradeoff between components reliabilityand redundancy levels, which is known as reliability-redundancy allocation problem (RRAP).
Keywords: Reliability-redundancy allocation problem; Cold-standby strategy; Reliability optimization; Water cycle algorithm.
The goal of the RAP is to find the optimal number of redundant components in each subsystem in order to maximize the overall system reliability whereas in the RRAP, the component reliability is a design variable and its characteristics are computed as increasing nonlinear functions of component reliability (Ardakan & Hamadani, 2014a).
, 2008), artificial neural networks (Habib, Alsieidi, & Youssef, 2009), particle swarm optimization (dos Santos Coelho, 2009), ant colony optimization (Liang & Smith, 2004; Nahas & Nourelfath, 2005) have been developed for solving different RRAP problems.
For solving the RRAP with the active redundant strategy, a two-phase approach based on an Immune Algorithm (IA) has been developed by Hsieh and You (2011) They implemented the IA in the first phase and developed a new procedure to improve the final solution in the second phase.
We can obtain the population of raindrops by representing a matrix of size (View the image of this page)The objective function calculates the reliability of each raindrop as follows: (View the image of this page) In the searching process of the algorithm, streams and rivers may violate the considered constraints of the problem.