Abstract
The chapter covers two main areas, these being an introduction to the technology and techniques associated with genetic algorithms and then the second part looks at how genetic algorithms can be used to search for good topological solutions to engineering design challenges. The start of the chapter places genetic algorithms in context compared to other evolutionary algorithms and also describes the reasons why genetic algorithms are potentially useful. This is then followed by a look at the concept of a search space. Section two looks at the canonical genetic algorithm as a basic introduction to the technology and includes an examination of the main techniques used to encode the genome, fitness functions, operators and selection. Section three looks at how genetic algorithms can be used for design and chooses the specific example of the conceptual design of commercial office buildings. Section four introduces the basic concepts of topological search and explains how having the right form of representation is vital before looking at example relating to structural components and the design of domes using a genetic algorithm linked to computational geometry techniques. The final section then looks at further methods using generative representations and generative geometries as possible solutions to the need to develop powerful forms of representation for handling topological search in genetic algorithms.
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Bibliography
Borkowski, A. and Grabska, E. (1995). Representing designs by composition graphs. In Smith, I., editor, Knowledge Support Systems in Civil Engineering, pages 27–36. IABSE, Zurich.
Bradshaw, J. (1996). Deriving strategies for reducing pollution damage using a genetic algorithm. Ph.D. thesis, Cardiff School of Engineering, Cardiff University.
Bradshaw, J. and Miles, J. (1997). Using standard fitnesses with genetic algorithms. Advances in Engineering Software.
Bucciarelli, L. and Sthapit, A. (accessed 2003). Trussworks 3d matrix truss analysis. web site 1, MIT.
de Berg, M. (2000). Computational geometry: algorithms and applications. Springer-Verlag, 1st edition.
Deb, K. and Gulati, S. (2001). Design of truss structures for minimum weight using genetic algorithms. Finite Element Analysis and Design.
Gere, J. and Timoshenko, S. (1997). Mechanics of materials. PWS publishing Company, 4th edition.
Goldberg, D. (1989). Genetic algorithms in search, optimization and machine Learning. Addison-Wesley, 1st edition.
Grierson, D. and Khajehpour, S. (2002). Method for conceptual design applied to office buildings. Journal of computing in civil engineering.
Griffiths, D. and Miles, J. (2003). Determining the optimal cross section of beams. Advanced Engineering Informatics.
Holland, J. (1975). Adaptation in natural and artificial systems. University of Michigan Press, 1st edition.
Hooper, J. (1993). A knowledge-based system for strategic sludge disposal planning. Ph.D. thesis, Cardiff School of Engineering, Cardiff University.
Hornby, G. (2003). Generative representations for evolutionary design automation. Ph.D. thesis, Brandeis University.
Khajehpour, S. and Grierson, D. (1999). Filtering of pareto optimal trade-off surfaces for building conceptual design. In Topping, B., editor, Optimization and control in civil and structural engineering, pages 63–70. Saxe-Coburg Press, Edinburgh.
Khajehpour, S. and Grierson, D. (2003). Profitability versus safety of high-rise office buildings. Journal of structural and multidisciplinary optimization.
Leyton, M. (2001). A generative theory of shape. Springer-Verlag, 1st edition.
Miles, J., Kwan, A., Wang, K. and Zhang, Y. (2007). Searching for good topological solutions using evolutionary algorithms. In Topping, B., editor, Civil engineering computations: Tools and Techniques, pages 149–172. Saxe-Coburg Press, Edinburgh.
Motro, R. (1994). Review of the development of geodesic domes. In Makowski, Z., editor, Analysis, design and construction of braced domes, pages 387–412. Cambridge University Press, Cambridge.
Parmee, I. (1998). Evolutionary and adaptive strategies for efficient search across whole system engineering design hierarchies. AIEDAM.
Parmee, I. (2001). Evolutionary and adaptive computing in engineering design. Springer-Verlag, 1st edition.
Richardson, J., Palmer, M., Liepens, G. and Hillyard, M. (1989). Some guidelines for genetic algorithms with penalty functions. In Anon, editor, Proc. 3rd Int. Conf. on genetic algorithms, pages 191–197. Morgan Kaufman, USA.
Rourke, J. O. (1998). Computational geometry in C. Cambridge University Press, 2nd edition.
Shamos, M. (1978). Computational Geometry. Ph.D. thesis, Yale University.
Shaw, D., Miles, J. and Gray, W. (2005a). Conceptual design of geodesic domes. In Topping, B., editor, Proc. 8th Int Conf on the Application of AI to Civil, Structural and Environmental Engineering. Saxe-Coburg, Edinburgh UK.
Shaw, D., Miles, J. and Gray, W. (2005b). Conceptual design of orthogonal commercial buildings. In Topping, B., editor, Proc. 8th Int Conf on the Application of AI to Civil, Structural and Environmental Engineering. Saxe-Coburg, Edinburgh UK.
Sisk, G. (1999). The use of a GA-Based DSS for realistically constrained building design. Ph.D. thesis, Cardiff University.
Weisstein, E. (accessed 2005). Circle point picking — mathworld — a wolfram web resource. web site 1, mathworld.wolfram.com/CirclePointPicking.html.
Wolpert, D. and MacReady, W. (1997). No free lunch theorems for optimization. IEEE Trans. on Evolutionary Computing.
Yang, Y. (2000). Genetic programming for structural optimization. Ph.D. thesis, Nanyang Technological University.
Zhang, Y. and Miles, J. (2004). Representing the problem domain in stochastic search algorithms. In Schnellenback-Held, M. and Hartmann, M., editors, Next generation intelligent systems in engineering, pages 156–168. EG-ICE, Essen.
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Miles, J. (2010). Genetic Algorithms for Design. In: Waszczyszyn, Z. (eds) Advances of Soft Computing in Engineering. CISM International Centre for Mechanical Sciences, vol 512. Springer, Vienna. https://doi.org/10.1007/978-3-211-99768-0_1
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DOI: https://doi.org/10.1007/978-3-211-99768-0_1
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