Abstract
In Chapter 6, the desired function and constraints are mapped to the artifact description using an evolutionary process that can be visualized as a feedback loop of analysis, synthesis and evaluation. In this chapter, we define “basic synthesis” as the complete description of ‘primitive’ components and their relations so as to meet a set of specifications of satisfactory performance. To determine if “basic synthesis” could scale up to large problems, it is appropriate to analyze the computational complexity of the “basic synthesis” task — an issue which has often been ignored by the design research community. A special case of the “basic synthesis” activity, called the Basic Synthesis Problem (BSP), is addressed. The BSP is shown to be NP-Complete, generally applicable over all design domains, which suggests that the combinatorial complexity would be exponential, hence intractable within most modern computing environments. Such a theoretical mathematical analysis ignores critical domain-specific engineering knowledge. We show that by combining domain-specific mechanical engineering heuristics, which constrain the structure of potential artifacts, the BSP will be computationally tractable. In order to demonstrate the guided heuristics approach to specific domains, the heuristically guided combinatorial analysis will be presented for 2-D wireframe feature recognition systems which are predominant in industrial CAD systems.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Garey, M.R. and Johnson, D.S., Computers and Intractability: A guide to the Theory of NP-Completeness. San Francisco: W. H. Freeman and Company, 1979.
Krishnamoorthy, C.S., Shivakumar, H., Rajeev S. and Suresh, S., “A Knowledge-Based Systems with Generic Tools for Structural Engineering,” Structural Engineering Review. Vol. 5 (1), 1993.
Simon, H.A., The Science of the Artificial. Cambridge. MA: MIT Press, 1981.
Cover, T. M. and J. A. Thomas, Elements of Information Theory. New York: Wiley and Sons, 1991.
Das, S. R., D. K. Banerji, and A. K. Chattopadhyay, “On Control Memory Minimization in Microprogrammed Digital Computers,” IEEE Transactions on Computers, Vol. C-22 (9), pp. 845–848, 1973.
Grasselli, A. and U. Montanan, “On the Minimization of Read-Only Memories in Microprogramed Digital Computers,” IEEE Transactions on Computers, Vol. C-19 (11), pp. 1111–1114, 1970.
Hayes, J. P., Computer Architecture and Organization. New York: McGraw-Hill, 1988.
Ullman, D., T. G. Dietterich, and L. A. Stauffer, “A Model of the Mechanical Design Process Based on Empirical Data,” AI EDAM, Vol. 2, pp. 33–52, 1988.
Rodrigues, W., The Modeling of Design Ideas. New York: McGraw-Hill, 1992.
Peters, T. J. “Mechanical Design Heuristics to Reduce the Combinatorial Complexity for Feature Recognition,” Research in Engineering Design, 1993.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 1998 Springer Science+Business Media Dordrecht
About this chapter
Cite this chapter
Braha, D., Maimon, O. (1998). Guided Heuristics in Engineering Design. In: A Mathematical Theory of Design: Foundations, Algorithms and Applications. Applied Optimization, vol 17. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-2872-9_7
Download citation
DOI: https://doi.org/10.1007/978-1-4757-2872-9_7
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4419-4798-7
Online ISBN: 978-1-4757-2872-9
eBook Packages: Springer Book Archive