A hyper-heuristic approach to aircraft structural design optimization

Allen, J.G.; Coates, G.; Trevelyan, J.

Abstract

The conceptual design of an aircraft is a challenging problem in which optimization can be of great importance to the quality of design generated. Mass optimization of the structural design of an aircraft aims to produce an airframe of minimal mass whilst maintaining satisfactory strength under various loading conditions due to flight and ground manoeuvres. Hyper-heuristic optimization is an evolving field of research wherein the optimization process is continuously adapted in order to provide greater improvements in the quality of the solution generated. The relative infancy of hyper-heuristic optimization has resulted in limited application within the field of aerospace design. This paper describes a framework for the mass optimization of the structural layout of an aircraft at the conceptual level of design employing a novel hyper-heuristic approach. This hyper-heuristic approach encourages solution space exploration, thus reducing the likelihood of premature convergence, and improves the feasibility of and convergence upon the best solution found. A case study is presented to illustrate the effects of hyper-heuristics on the problem for a large commercial aircraft. Resulting solutions were generated of considerably lighter mass than the baseline aircraft. A further improvement in solution quality was found with the use of the hyper-heuristics compared to that obtained without, albeit with a penalty on computation time.

Citation

Allen, J., Coates, G., & Trevelyan, J. (2013). A hyper-heuristic approach to aircraft structural design optimization. Structural and Multidisciplinary Optimization, 48(4), 807-819. https://doi.org/10.1007/s00158-013-0928-3

• Journal Article Type: Article
• Publication Date: Oct 1, 2013
• Deposit Date: Oct 3, 2012
• Publicly Available Date: Jun 9, 2014
• Journal: Structural and Multidisciplinary Optimization
• Print ISSN: 1615-147X
• Electronic ISSN: 1615-1488
• Publisher: Springer
• Peer Reviewed: Peer Reviewed
• Volume: 48
• Issue: 4
• Pages: 807-819
• DOI: https://doi.org/10.1007/s00158-013-0928-3
• Public URL: https://durham-repository.worktribe.com/output/1472619