Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/2323
Title: Searching for improvement
Authors: Atherton, MA
Bates, RA
Issue Date: 2006
Publisher: WIT Press
Citation: In: Bryant, J, A, Atherton, M, A and Collins, M, W (eds). Information transfer in biological systems, Design in nature series volume 2. Southampton: WIT Press, 2006
Abstract: Engineering design can be thought of as a search for the best solutions to engineering problems. To perform an effective search, one must distinguish between competing designs and establish a measure of design quality, or fitness. To compare different designs, their features must be adequately described in a well-defined framework, which can mean separating the creative and analytical parts of the design process. By this we mean that a distinction is drawn between coming up with novel design concepts, or architectures, and the process of detailing or refining existing design architecture. In the case of a given design architecture, one can consider the set of all possible designs that could be created by varying its features. If it were possible to measure the fitness of all designs in this set, then one could identify a fitness landscape and search for the best possible solution for this design architecture. In this Chapter, the significance of the interactions between design features in defining the metaphorical fitness landscape is described. This highlights that the efficiency of a search algorithm is inextricably linked to the problem structure (and hence the landscape). Two approaches, namely, Genetic Algorithms (GA) and Robust Engineering Design (RED) are considered in some detail with reference to a case study on improving the design of cardiovascular stents.
URI: http://bura.brunel.ac.uk/handle/2438/2323
ISBN: 1853128538
Appears in Collections:Design
Mechanical and Aerospace Engineering
Dept of Mechanical Aerospace and Civil Engineering Research Papers

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