Evolutionary methods for multidisciplinary optimization applied to the design of UAV systems

• Published in: Engineering optimization Vol. 39; no. 7; pp. 773 - 795
• Main Authors: Gonzalez, L.F., Periaux, J., Damp, L., Srinivas, K.
• Format: Journal Article
• Language: English
• Published: Taylor & Francis 01.10.2007
• Subjects: Aerostructural optimization; Game theory; Multi-criteria evolutionary algorithms
• ISSN: 0305-215X; 1029-0273
• DOI: 10.1080/03052150701515037

The implementation and use of a framework in which engineering optimization problems can be analysed are described. In the first part, the foundations of the framework and the hierarchical asynchronous parallel multi-objective evolutionary algorithms (HAPMOEAs) are presented. These are based upon evolution strategies and incorporate the concepts of multi-objective optimization, hierarchical topology, asynchronous evaluation of candidate solutions, and parallel computing. The methodology is presented first and the potential of HAPMOEAs for solving multi-criteria optimization problems is demonstrated on test case problems of increasing difficulty. In the second part of the article several recent applications of multi-objective and multidisciplinary optimization (MO) are described. These illustrate the capabilities of the framework and methodology for the design of UAV and UCAV systems. The application presented deals with a two-objective (drag and weight) UAV wing plan-form optimization. The basic concepts are refined and more sophisticated software and design tools with low- and high-fidelity CFD and FEA models are introduced. Various features described in the text are used to meet the challenge in optimization presented by these test cases.