TY - JOUR
T1 - A multi-objective reliability optimization for reconfigurable systems considering components degradation
AU - Zhao, Jiangbin
AU - Si, Shubin
AU - Cai, Zhiqiang
N1 - Publisher Copyright:
© 2018 Elsevier Ltd
PY - 2019/3
Y1 - 2019/3
N2 - Reconfigurable systems have been widely used in practical engineering, especially for the reconfigurable computing systems and reconfigurable manufacturing systems. The reliability of reconfigurable systems can be improved by components replacement or components rearrangement without changing their reliability. Combining the advantages of the rearrangement method and replacement method, an integrated method is proposed to improve the reconfigurable system reliability cost-effectively in this paper. Then, a 0–1 integer programming model of multi-objective optimization is established to obtain the reconfiguration with maximum system reliability and minimum reconfiguration cost based on the integrated method. The coarse-grained parallel genetic algorithm (CPGA) is introduced to solve the multi-objective model, while the multiple objectives problem can be converted into a single objective problem through the novel fitness function. Finally, three examples based on the production monitoring system are implemented to illustrate the effectiveness of the CPGA comparing with the replacement based genetic algorithm. The changes of optimal reconfigurations with different parameters of the fitness function and different pre-determined system reliability are also discussed based on the examples.
AB - Reconfigurable systems have been widely used in practical engineering, especially for the reconfigurable computing systems and reconfigurable manufacturing systems. The reliability of reconfigurable systems can be improved by components replacement or components rearrangement without changing their reliability. Combining the advantages of the rearrangement method and replacement method, an integrated method is proposed to improve the reconfigurable system reliability cost-effectively in this paper. Then, a 0–1 integer programming model of multi-objective optimization is established to obtain the reconfiguration with maximum system reliability and minimum reconfiguration cost based on the integrated method. The coarse-grained parallel genetic algorithm (CPGA) is introduced to solve the multi-objective model, while the multiple objectives problem can be converted into a single objective problem through the novel fitness function. Finally, three examples based on the production monitoring system are implemented to illustrate the effectiveness of the CPGA comparing with the replacement based genetic algorithm. The changes of optimal reconfigurations with different parameters of the fitness function and different pre-determined system reliability are also discussed based on the examples.
KW - Multi-objective optimization
KW - Parallel genetic algorithm
KW - Reconfigurable system
KW - Reconfiguration cost
UR - http://www.scopus.com/inward/record.url?scp=85056651618&partnerID=8YFLogxK
U2 - 10.1016/j.ress.2018.11.001
DO - 10.1016/j.ress.2018.11.001
M3 - 文章
AN - SCOPUS:85056651618
SN - 0951-8320
VL - 183
SP - 104
EP - 115
JO - Reliability Engineering and System Safety
JF - Reliability Engineering and System Safety
ER -