Execution Plan Optimization and Consistency

Author(s):  
Sam R. Alapati ◽  
Darl Kuhn ◽  
Bill Padfield
Author(s):  
Sam R. Alapati ◽  
Darl Kuhn ◽  
Bill Padfield

2021 ◽  
Vol 22 (10) ◽  
pp. 329-337
Author(s):  
Huaizhi Geng ◽  
Tawfik Giaddui ◽  
Chingyun Cheng ◽  
Haoyu Zhong ◽  
Samuel Ryu ◽  
...  

2020 ◽  
Vol 152 ◽  
pp. S51-S52
Author(s):  
H. Langendijk ◽  
L. Van den Bosch ◽  
A. Van den Hoek ◽  
E. Oldehinkel ◽  
T. Meijer ◽  
...  

2021 ◽  
Author(s):  
Lu Chen ◽  
Guoqing Yu ◽  
Jie Song ◽  
Xiao Zhang

2018 ◽  
Vol 3 (3) ◽  
pp. 32 ◽  
Author(s):  
Shane Haladuick ◽  
Markus Dann

For engineering systems, decision analysis can be used to determine the optimal decision from a set of options via utility maximization. Applied to inspection and maintenance planning, decision analysis can determine the best inspection and maintenance plan to follow. Decision analysis is relatively straightforward for simple systems. However, for more complex systems with many components or defects, the set of all possible inspection and maintenance plans can be very large. This paper presents the use of a genetic algorithm to perform inspection and maintenance plan optimization for complex systems. The performance of the genetic algorithm is compared to optimization by exhaustive search. A numerical example of life cycle maintenance planning for a corroding pressure vessel is used to illustrate the method. Genetic algorithms are found to be an effective approach to reduce the computational demand of solving complex inspection and maintenance optimizations.


2011 ◽  
Vol 81 (2) ◽  
pp. S801-S802
Author(s):  
A.F. Uribe-Sanchez ◽  
X. Jia ◽  
C. Men ◽  
S. Jiang
Keyword(s):  

2016 ◽  
Author(s):  
Mohammad Yunus Khan ◽  
Anupam Tiwari ◽  
Shuichiro Ikeda ◽  
Fahad I. Syed ◽  
Alunood K. Al Sowaidi ◽  
...  

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