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244. Flight test scheduling: An integer programming model and a large neighborhood search algorithm
Invited abstract in session TC-60: Advanced heuristics for machine scheduling, stream Project Management and Scheduling.
Tuesday, 12:30-14:00Room: S09 (building: 101)
Authors (first author is the speaker)
| 1. | Guopeng Song
|
| National University of Defense Technology | |
| 2. | Hanqiao Tao
|
| National University of Defense Technology | |
| 3. | Roel Leus
|
| ORSTAT, KU Leuven |
Abstract
Flight tests play a critical role in the research and development of new aircraft as they help verify the airworthiness and capabilities and expose design and manufacturing defects. During the test course, a large number of test tasks need to be scheduled appropriately so that the flight tests can be completed with minimum cost and high efficiency. Therefore, there is a strong need for developing an efficient method that can generate high-quality test schedules. In this paper, we study the flight test scheduling problem to minimize the number of required test flights, thereby decreasing the cost and time required during the entire test course. We establish a mixed-integer programming model to formally describe the problem, propose several computationally efficient lower bounds to help verify the quality of obtained solutions, and develop a large neighborhood search algorithm for generating a high-quality solution of the flight test scheduling problem effectively. Comprehensive computational experiments are performed to demonstrate the efficiency of our proposed algorithm. We report some general managerial insights based on the obtained computational results.
Keywords
- Scheduling
- Programming, Integer
- Metaheuristics
Status: accepted
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