Abstract
In this chapter the use of Genetic Algorithms and Genetic Programming for various industrial problems is discussed. Particular attention is paid to the case of difficult design optimization problems in which either (or both) (i) response functions are computationally expensive as well as affected by numerical noise and (ii) design variables are defined on a set of discrete variables.
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Toropov, V.V., Alvarez, L.F., Querin, O.M. (2010). Applications of GA and GP to Industrial Design Optimization and Inverse Problems. 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_3
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