An improved genetic algorithm for flight test subject allocation problem

• Published in: IEEE/AIAA Digital Avionics Systems Conference pp. 1 - 6
• Main Authors: Liu, Yibo, Xiao, Gang, Wang, Miao
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.09.2019
• Subjects: Aircraft; Costs; Design methodology; Encoding; Flight Test; Flight Test Subject; Flight Test Subject Allocation; Genetic Algorithm; Genetic algorithms; Iterative algorithms; Optimization; Planning; Resource management; Technical requirements
• ISSN: 2155-7209
• DOI: 10.1109/DASC43569.2019.9081633

The civil aircraft flight test technology is complex and related to a large number of systems. The efficiency of the flight test task planning has become one of the key factors affecting the flight test duration and cost. In the initial planning process of the flight test task, the allocation of a large number of flight test subjects on multiple test aircrafts is a key issue. Through the research on the workflow of the current civil flight test and the characteristics of the flight test subject, this paper analyzes the basic constraints in the initial stage of the flight test task planning and the key factors related to the total duration of the flight test task. Based on above, the subject allocation problem is reduced to a combination optimization problem. Due to the unique constraints of this problem, this paper designs a method based on improved genetic algorithm to generate the flight test subject allocation scheme, satisfactory results were achieved with all constraints met.