A Genetic Algorithm for Scheduling and Decomposition of Multidisciplinary Design Problems

[+] Author and Article Information
Stephen S. Altus, Ilan M. Kroo, Peter J. Gage

Aircraft Aerodynamics and Design Group Department of Aeronautics and Astronautics, Stanford University, Stanford, CA 94305

J. Mech. Des 118(4), 486-489 (Dec 01, 1996) (4 pages) doi:10.1115/1.2826916 History: Received July 01, 1995; Revised May 01, 1996; Online December 11, 2007


Complex engineering studies typically involve hundreds of analysis routines and thousands of variables. The sequence of operations used to evaluate a design strongly affects the speed of each analysis cycle. This influence is particularly important when numerical optimization is used, because convergence generally requires many iterations. Moreover, it is common for disciplinary teams to work simultaneously on different aspects of a complex design. This practice requires decomposition of the analysis into subtasks, and the efficiency of the design process critically depends on the quality of the decomposition achieved. This paper describes the development of software to plan multidisciplinary design studies. A genetic algorithm is used, both to arrange analysis subroutines for efficient execution, and to decompose the task into subproblems. The new planning tool is compared with an existing heuristic method. It produces superior results when the same merit function is used, and it can readily address a wider range of planning objectives.

Copyright © 1996 by The American Society of Mechanical Engineers
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