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Title: Genetic algorithms for evolutionary product design
Author: Graham, Ian J.
ISNI:       0000 0001 3509 5706
Awarding Body: Loughborough University
Current Institution: Loughborough University
Date of Award: 2002
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This thesis describes research into the development of a Computer Aided Design (CAD) tool that uses a Genetic Algorithm (GA) to generate and evolve original design concepts through human interaction. CAD technologies are firmly established in the later stages of design, and include many applications of Evolutionary Algorithms (EAs). The use of EAs as generative and search tools for conceptual design is less evident in fields other than abstract art, architecture and styling. This research gains its originality in aiming to assist designers early in the design process, by creating and evolving aesthetically interesting forms (objects). The integration of GA software with a solid modelling system has enabled the development of a prototype `Evolutionary Form Design' (EFD) system. Objects are defined using a genetic data structure and constructed from various geometric primitives and combinations of Boolean operators. The primitives interact in ways that are not easily predicted, often creating novel shapes that are unlikely to have been discovered through conventional means. Edge blending further adds to objects' complexity and visual appeal. Populations of objects are subjected to a `selective breeding' programme, directed through the user's allocation of scores, and may also be guided by simple geometric targets. These factors determine which objects are `fittest' and most likely to parent a new, hopefully improved generation of objects. The challenge has been to turn the concept into a genuinely useful tool, ensuring that desirable features are reproduced in subsequent populations. The key to achieving this is the way objects are recombined during reproduction. Work has included developing 4 novel routine for grouping the individual primitives that form objects using a Teamforming algorithm. Innovative, aesthetically interesting forms can be evolved intuitively and efficiently, providing inspiration and the initial models for original design concepts. Examples are given where the system'is used by undergraduates to generate seating designs, and by the author, to create virtual sculptures and a range of consumer product concepts.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Genetic algorithms ; Interactive ; Evolutionary design ; Conceptual form ; Aesthetic