By Mary Lou Maher, Josiah Poon, Sylvie Boulanger (auth.), John S. Gero, Fay Sudweeks (eds.)
Designing is without doubt one of the most vital of human acts. strangely, provided that designing has been happening for lots of millenia, our realizing of the techniques of designing is remarkably constrained. lately, layout tools were formalised no longer as humano-centred strategies yet as procedures in a position to machine implementation with the target of augmenting human designers. This quantity comprises contributions which conceal layout tools in accordance with evolutionary structures, generative techniques, evaluate equipment and research equipment. It provides the state-of-the-art in formal layout tools for laptop aided design.
Read Online or Download Advances in Formal Design Methods for CAD: Proceedings of the IFIP WG5.2 Workshop on Formal Design Methods for Computer-Aided Design, June 1995 PDF
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Additional resources for Advances in Formal Design Methods for CAD: Proceedings of the IFIP WG5.2 Workshop on Formal Design Methods for Computer-Aided Design, June 1995
1991, Exploration and Innovation in Design, Springer-Verlag, New York. Simon, H. , Cambridge, Mass Watabe, H. : 1993, Structural shape optimization by multi-species genetic algorithm, in C. Rowles, H. Liu and N. Foo (eds), Proceedings of the 6th Australian Joint Conference on Artificial Intelligence (AI'93) , Melbourne, Australia, pp. 109-116. FORMALISING DESIGN EXPLORATION AS CO-EVOLUTION 27 Appendix: Evaluation functions for braced frame design There are four evaluation functions used in this example for evaluating the performance of a braced frame: fO: f2: f3: f4: measure of closeness to initial requirements, measure of conformance to bay layout measure of structural efficiency measure of structural integrity The first function, fo, uses a combination of three functions, each concentrating on measuring the distance between the current phenotype and the one problem parameter in the initial requirements.
0 z >= 0 ~ u. 1 I 0 0 20 40 ",r so BO 100 GENERATIONS 120 1S0 140 1BO Figure 13. The fraction of composite building blocks with different complexities in the total pool of the building block used to assemble the population vs. generation number in the experiment. J (L ::;; 0 0 u. 5 If generation 0 is filtered by Fi, this tendency is present but not as strong. For instance, applying the initial Fi may reduce the overall Fg value from generation o to generation 1, but at least, finit has a better probability of being favoured although its value at generation 1 is low. This may influence the number of generations until convergence but not the pattern of exploration. The quality of the evaluation functions in terms of how they relate to each other and not just how adequately they attribute a value within one evaluation function is important.
If generation 0 is filtered by Fi, this tendency is present but not as strong. For instance, applying the initial Fi may reduce the overall Fg value from generation o to generation 1, but at least, finit has a better probability of being favoured although its value at generation 1 is low. This may influence the number of generations until convergence but not the pattern of exploration. The quality of the evaluation functions in terms of how they relate to each other and not just how adequately they attribute a value within one evaluation function is important.