Prior to the early 1990s the term 'evolutionary computing' (EC) would have meant little to most practising engineers unless they had a particular interest in emerging computing technologies or were part of an organisation with significant in-house research activities. It was around this time that the first tentative utilisation of relatively simple evolutionary algorithms within engineering design began to emerge in the UK The potential was rapidly recognised especially within the aerospace sector with both Rolls Royce and British Aerospace taking a serious interest while in the USA General Electric had already developed a suite of optimisation software which included evolutionary and adaptiv,e search algorithms. Considering that the technologies were already twenty-plus years old at this point the long gestation period is perhaps indicative of the problems associated with their real-world implementation. Engineering application was evident as early as the mid-sixties when the founders of the various techniques achieved some success with computing resources that had difficulty coping with the population-based search characteristics of the evolutionary algorithms. Unlike more conventional, deterministic optimisation procedures, evolutionary algorithms search from a population of possible solutions which evolve over many generations. This largely stochastic process demands serious computing capability especially where objective functions involve complex iterative mathematical procedures.
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Evolutionary and Adaptive Computing in Engineering Design Aims to raise designers' and researchers' awareness of the potential of evolutionary and adaptive computing within engineering design. Generic problem areas investigated include: design decomposition; whole-system design; multi-objective and constraint satisfaction; human-computer interaction; and computational expense.
The overall purpose of the book is to raise designers' and researchers' awareness of the potential of evolutionary and adaptive computing within engineering design. Although there are many examples of the application of evolutionary and adaptive search algorithms to well-defined engineering design problems, examples exploring the generic utility of these techniques across the design process as a whole are less evident. Experience of the integration of the technology with conceptual, embodiment and detailed design processes indicates that, in addition to routine optimisation, the powerful search and exploration capabilities of the various techniques coupled with appropriate designer interaction can lead to the discovery of high-performance, innovative design alternatives. Following an introduction to the various techniques and examples of their routine application, this potential is explored through the introduction of various strategies that support searches across a far broader set of possible design solutions within time and budget constraints.
Generic problem areas investigated include: design decomposition; whole-system design; multi-objective and constraint satisfaction; human-computer interaction; computational expense. These stem from across the mechanical, civil, electronic, aerospace and power system engineering sectors. Appropriate strategies that help overcome problems often encountered when integrating computer-based techniques with complex, real-world design environments are described. A straightforward approach coupled with examples supports a rapid understanding of the manner in which such strategies can best be designed to handle the complexities of a particular problem."About this title" may belong to another edition of this title.
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