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Evolutionary and Adaptive Computing in Engineering Design

  • Book
  • © 2001

Overview

Authors:
  1. Ian C. Parmee

    1. Advanced Computational Technologies, Exeter, UK

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  • Presents research carried out at the Engineering Design Centre in Plymouth, one of six national centres designated for university-based engineering design in the UK
  • Moves from research in specific areas to the utility of evolutionary/adaptive search within engineering design as a whole
  • The application of genetic and soft-computing techniques in all areas of engineering is becoming the first port of call for most academic and many practising engineers

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Table of contents (13 chapters)

  1. Front Matter

    Pages i-xvi
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  2. Introduction

    • Ian C. Parmee
    Pages 1-15

  3. Established Evolutionary Search Algorithms

    • Ian C. Parmee
    Pages 17-44

  4. Adaptive Search and Optimisation Algorithms

    • Ian C. Parmee
    Pages 45-57

  5. Initial Application

    • Ian C. Parmee
    Pages 59-77

  6. The Development of Evolutionary and Adaptive Search Strategies for Engineering Design

    • Ian C. Parmee
    Pages 79-87

  7. Evolutionary Design Space Decomposition

    • Ian C. Parmee
    Pages 89-109

  8. Whole-system Design

    • Ian C. Parmee
    Pages 111-131

  9. Variable-length Hierarchies and System Identification

    • Ian C. Parmee
    Pages 133-150

  10. Evolutionary Constraint Satisfaction and Constrained Optimisation

    • Ian C. Parmee
    Pages 151-175

  11. Multi-objective Satisfaction and Optimisation

    • Ian C. Parmee
    Pages 177-203

  12. Towards Interactive Evolutionary Design Systems

    • Ian C. Parmee
    Pages 205-231

  13. Population-based Search, Shape Optimisation and Computational Expense

    • Ian C. Parmee
    Pages 233-251

  14. Closing Discussion

    • Ian C. Parmee
    Pages 253-259

  15. Back Matter

    Pages 261-286
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Keywords

About this book

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.

Authors and Affiliations

  • Advanced Computational Technologies, Exeter, UK

    Ian C. Parmee

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