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Research Papers

Exploring the Effectiveness of Using Graveyard Data When Generating Design Alternatives

[+] Author and Article Information
Garrett Foster

Research Assistant
e-mail: gdfoster@ncsu.edu

Scott Ferguson

Assistant Professor
e-mail: scott_ferguson@ncsu.edu
North Carolina State University,
Department of Mechanical and Aerospace
Engineering Raleigh, NC 27695

Contributed by the Computers and Information Division of ASME for publication in the Journal of Computing and Information Science in Engineering. Manuscript received January 11, 2013; final manuscript received June 7, 2013; published online August 19, 2013. Assoc. Editor: Joshua D. Summers.

J. Comput. Inf. Sci. Eng 13(4), 041003 (Aug 19, 2013) (11 pages) Paper No: JCISE-13-1006; doi: 10.1115/1.4024913 History: Received January 11, 2013; Revised June 07, 2013

The objective of this paper is to demonstrate that unique alternative designs can be efficiently found by searching the discarded data (or graveyard) from a multiobjective genetic algorithm (MOGA). Motivation for using graveyard data to generate design alternatives arises from the computational cost associated with real-time design space exploration of multiobjective optimization problems. The effectiveness of this approach is explored by comparing (1) the uniqueness of alternatives found using graveyard data and those generated using an optimization-based search, and (2) how alternative generation near the Pareto frontier is impacted. Two multiobjective case study problems are introduced—a two bar truss and an I-beam design optimization. Results from these studies indicate that using graveyard data allows for the discovery of alternative designs that are at least 70% as unique as alternatives found using an optimization-based alternative identification approach, while saving a significant number of functional evaluations. Additionally, graveyard data are shown to be better suited for alternative generation near the Pareto frontier than standard sampling techniques. Finally, areas of future work are also discussed.

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Grahic Jump Location
Fig. 3

Illustration of percent change calculation

Grahic Jump Location
Fig. 1

Diagram of two bar truss

Grahic Jump Location
Fig. 2

Cross section of I-beam

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