An optimization approach for DAL assignments
Aircraft Engineering and Aerospace Technology
ISSN: 0002-2667
Article publication date: 5 March 2018
Abstract
Purpose
Development assurance level (DAL) is the measurement of the rigor of development assurance tasks performed to functions or items. The DAL assignment is an important process of aircraft system development that can make the reliability and safety of the system stay at acceptable levels. This paper aims to propose an optimization approach for the DAL assignments to minimize the development cost of aircraft systems.
Design/methodology/approach
The mathematical model for the DAL assignment optimization has been developed on the basis of the given expressions of objective function and constraints. In addition, a hybrid algorithm model synthesizing the advantages of genetic algorithm (GA) and Tabu search (TS) has been proposed to solve the optimization problem of the DAL assignment.
Findings
The results of the case study show that the proposed hybrid algorithm is more efficient and effective than the exhaustive method as well as the pure GA.
Practical implications
The proposed approach can be applied in the development of aircraft systems, and it has great significance in minimizing the development cost as well as keeping the system reliability and safety at an acceptable level.
Originality/value
The constrained optimization method has been applied in the DAL assignments, the corresponding mathematical model has been built and a hybrid evolutionary algorithm has been proposed to solve the optimization problem.
Keywords
Acknowledgements
The authors wish to appreciate the support from National Natural Science Foundation of China (61403192 and U1333118) and Natural Science Foundation of Jiangsu Province (BK20130811).
Citation
Li, X., Lu, Z. and Wang, J. (2018), "An optimization approach for DAL assignments", Aircraft Engineering and Aerospace Technology, Vol. 90 No. 2, pp. 328-335. https://doi.org/10.1108/AEAT-10-2016-0167
Publisher
:Emerald Publishing Limited
Copyright © 2018, Emerald Publishing Limited