Evolutionary and Adaptive Computing in Engineering Design

Parmee, Ian C.

ISBN 10: 1447110617 / ISBN 13: 9781447110613

Edité par Springer, 2012

N° de réf. du vendeur 19199637-n

Synopsis :

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.

Présentation de l'éditeur: 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. 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.

Détails bibliographiques

Titre : Evolutionary and Adaptive Computing in ...
Éditeur : Springer
Date d'édition : 2012
Reliure : Couverture souple
Etat : New