Abstract
Article history: Received October 29, 2014 Received in revised format: March 2, 2015 Accepted April 22, 2015 Available online April 25 2015 Reliability is one of the most important characteristics of the electrical and mechanical systems with applications in the space communication industries, internet networks, telecommunication systems, power generation systems, and productive facilities. What adds to the importance of reliability in these systems are system complications, nature of competitive markets, and increasing production costs due to failures. This paper investigates availability optimization of a system using both repairable and non-repairable components, simultaneously. The availability-redundancy allocation problems involve the determination of component availability (i.e., life time and repair time of the components) and the redundancy levels that produce maximum system availability. These problems are often subject to some constraints on their components such as cost, weight, and volume. To maximize the availability and to minimize the total cost of the system, a new Mixed Integer Nonlinear Programming (MINLP) model is presented. To solve the proposed model, an improved version of the genetic algorithm is designed as an efficient meta-heuristic algorithm. Finally, in order to verify the efficiency of the proposed algorithm, a numerical example of a system is presented that consists of both repairable and non-repairable components. Growing Science Ltd. All rights reserved. 5 © 201
Highlights
Reliability optimization is an important topic that has attracted the attention of many researchers
To solve the proposed mathematical model and to show the capability of the proposed Genetic Algorithm (GA) in handling the problem, a modified problem from the literature is considered and the GA results are compared with those of the Improved Particle Swarm Optimization (IPSO) algorithm (Wu et al, 2011) as one of the best algorithms reported in the literature
In order to show the capability of the genetic algorithm, the problem has been solved by the Improved Particle Swarm Optimization (IPSO) algorithm proposed in Wu et al (2011), which is considered as one of the best algorithms in Redundancy Allocation Problem (RAP) so far
Summary
Reliability optimization is an important topic that has attracted the attention of many researchers. The Reliability-Redundancy Allocation Problem (RRAP) is formulated as a mixed-integer non-linear programming problem It is a more complicated version compared with the RAP since the reliability and, other related specifications of the components are not predetermined and considered as decision variables. The purpose of RRAP is to maximize system reliability by selecting component reliability and component redundancy levels, which forms a difficult but realistic optimization problem Component specifications such as cost, weight, and volume are defined as increasing non-linear functions of component reliability (Coit, 2003). This paper deals with the RRAPs whose main difference from similar problems lies in the assumption that the system involves both repairable and non-repairable components; it must be considered as ARAP To solve this problem, a new mixed integer non-linear programming model is introduced and solved by an improved version of Genetic Algorithm (GA). The paper concludes with results, conclusions, and some suggestions for future study
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