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Global optimization and Evolutionary Search
Published in Yi Chen, Yun Li, Computational Intelligence Assisted Design, 2018
Evolutionary computation, artificial neural network and fuzzy‐logic‐based soft-computing paradigms mimic human evolution, learning and decision‐making and offer tractable solutions to real‐world problems. For example, in evolutionary computation, the power of multiple trial‐and‐error based a posteriori ‘intelligence’ is utilized to test and discover possible solutions to many conventionally unsolvable problems. When interfaced with an existing CAD package, an evolutionary algorithm (EA) enables computer‐automated design (CAutoD) by extending passive CAD simulation into active design search.
Virtual Reality design-build-test games with physics simulation: opportunities for researching design cognition
Published in International Journal of Design Creativity and Innovation, 2021
Maria Adriana Neroni, Alfred Oti, Nathan Crilly
Digital prototyping involves the use of computer-aided design (CAD), computer-automated design (CAutoD) and computer-aided engineering (CAE) software to create, modify and analyze digital models. Some of the benefits that digital prototyping tools have over physical model making include increased productivity, increased design quality and simulation possibilities (e.g., see Colln et al., 2012; Islamoglu & Deger, 2015; Negendahl, 2015). Design research has mainly analyzed the impact of digital prototypes on design processes and design outcomes. For example, the use of CAD models was found to facilitate visualization of design concepts and designers’ reflection (e.g., see Schon & Wiggins, 1992; Suwa & Tversky, 1997). However, CAD tools are also associated with promoting bounded ideation and premature fixation to early design concepts (e.g., see Robertson et al., 2007). These drawbacks have mainly been attributed to the use of complex interfaces which do not assist the evolution and pace of designers’ thoughts (e.g., see Israel et al., 2009) and to overly-defined models which lead designers to commit to decisions prematurely, preventing the exploration of alternative ideas (Chandrasekera, 2015).