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Integrating a Genetic Algorithm Into a Knowledge-Based System for Ordering Complex Design ProcessesThe design cycle associated with large engineering systems requires an initial decomposition of the complex system into design processes which are coupled through the transference of output data. Some of these design processes may be grouped into iterative subcycles. In analyzing or optimizing such a coupled system, it is essential to be able to determine the best ordering of the processes within these subcycles to reduce design cycle time and cost. Many decomposition approaches assume the capability is available to determine what design processes and couplings exist and what order of execution will be imposed during the design cycle. Unfortunately, this is often a complex problem and beyond the capabilities of a human design manager. A new feature, a genetic algorithm, has been added to DeMAID (Design Manager's Aid for Intelligent Decomposition) to allow the design manager to rapidly examine many different combinations of ordering processes in an iterative subcycle and to optimize the ordering based on cost, time, and iteration requirements. Two sample test cases are presented to show the effects of optimizing the ordering with a genetic algorithm.
Document ID
19960021052
Document Type
Conference Paper
Authors
Rogers, James L. (NASA Langley Research Center Hampton, VA United States)
McCulley, Collin M. (State Univ. of New York Buffalo, NY United States)
Bloebaum, Christina L. (State Univ. of New York Buffalo, NY United States)
Date Acquired
September 6, 2013
Publication Date
April 1, 1996
Subject Category
Aircraft Design, Testing and Performance
Report/Patent Number
NASA-TM-110247
NAS 1.15:110247
Meeting Information
Artificial Intelligence in Design Conference(Stanford, CA)
Funding Number(s)
PROJECT: RTOP 509-10-11-01
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.

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