1
Industrial Engineering, Islamic Azad University, Qazvin Branch
2
Industrial Engineering, Sharif University of Technology
Abstract
The redundancy allocation is one of the most important and useful problems in system optimization, especially in electrical and mechanical systems. The object of this problem is to maximize system reliability or availability within a minimum operation cost. Many works have been proposed in this area so far to draw the problem near to real-world situations. While in classic models the system components are assumed to have two states of working and failed, in this paper, parallel components of serial sub-systems are considered to work in three states, each with a certain performance rate. The component states are classified into two working states of working with full performance and working with half performance, and a failed state. Besides, technical and organizational activities are considered to improve the performance of the components as well as the sub-systems. As the problem belongs to the class of NP-Hard, a genetic algorithm is utilized to solve it.
Zaretalab, A., Niaki, S., Sharifi, M., & Pourkarim Guilani, P. (2014). Redundancy Allocation Problem of a System with Three-state Components: A Genetic Algorithm (RESEARCH NOTE). International Journal of Engineering, 27(11), 1663-1672.
MLA
Arash Zaretalab; S.T.A. Niaki; Mani Sharifi; Pedram Pourkarim Guilani. "Redundancy Allocation Problem of a System with Three-state Components: A Genetic Algorithm (RESEARCH NOTE)". International Journal of Engineering, 27, 11, 2014, 1663-1672.
HARVARD
Zaretalab, A., Niaki, S., Sharifi, M., Pourkarim Guilani, P. (2014). 'Redundancy Allocation Problem of a System with Three-state Components: A Genetic Algorithm (RESEARCH NOTE)', International Journal of Engineering, 27(11), pp. 1663-1672.
VANCOUVER
Zaretalab, A., Niaki, S., Sharifi, M., Pourkarim Guilani, P. Redundancy Allocation Problem of a System with Three-state Components: A Genetic Algorithm (RESEARCH NOTE). International Journal of Engineering, 2014; 27(11): 1663-1672.
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