Overview

This collection of selected papers from the Fourth International Conference on Adaptive Computing in Design and Manufacture (ACDM0) represents a cross-section of the state-of-the art relating to the integration of advanced stochastic search, exploration and optimisation techniques with complex problem areas relating to various aspects of design and manufacturing processes. The Conference, held in the Sherwell Conference Centre at the University of Plymouth, Devon, UK in April, 2000, is a well-established biennial event supported by several UK Engineering Institutions and recognised by the International Society for Genetic and Evolutionary Computation as a mainstream event. The conference continues to attract an international audience of leading researchers and practitioners in the field. Aerospace, mechanical, thermal and structural design are among the subjects treated. In terms of manufacturing processes, cell formation, facility design, system control and robotics are addressed. In most cases, results from their application to or integration with real-world industrial problems are very much in evidence and conclusions relating to the overall utility of the various techniques across a diverse spectrum of problem areas are available. Evolutionary computing research and its application provides the mainstay in the great majority of papers. In the tradition of the ACDM series, papers utilising neural computing technologies and related computational intelligence techniques within the design/manufacture environments have also been included. The collection further illustrates the increasing uptake of these technologies in terms of academic research, academic and industrial collaboration and industrial practice. It is apparent that application strategies are becoming increasingly sophisticated as the powerful data processing capabilities of the technologies become more apparent and their increasing potential leads to integration with more complex problem areas so the book will be of particular interest to both design and computer science research communities in addition to those industrial organisations that are either already including these technologies in day-to-day working practice or that wish to familiarise themselves with the potential utility of their application further.

Full Product Details

Author:   I.C. Parmee
Publisher:   Springer London Ltd
Imprint:   Springer London Ltd
Edition:   Softcover reprint of the original 1st ed. 2000
Dimensions:   Width: 15.50cm , Height: 2.00cm , Length: 23.50cm
Weight:   0.587kg
ISBN:  

9781852333003

ISBN 10:   1852333006
Pages:   372
Publication Date:   12 April 2000
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Out of stock  
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Table of Contents

1. Engineering Design Applications.- 1.1 Optimisation of Power Plant Design: Stochastic and Adaptive Solution Concepts.- 1.2 Intelligent Searcher for the Configuration of Power Transmission Shafts in Gearboxes.- 1.3 Post-Processing of the Two-dimensional Evolutionary Structural Optimisation Topologies.- 1.4 Optimisation of a Stator Blade Used in a Transonic Compressor Cascade with Evolution Strategies.- 1.5 Mixed-integer Evolution Strategy for Chemical Plant Optimization with Simulators.- 1.6 Advantages in Using a Stock Spring Selection Tool that Manages the Uncertainty of the Designer Requirements.- 2. General Design Applications.- 2.1 Designing Food with Bayesian Belief Networks.- 2.2 Flexible Ligand Docking Using a Robust Evolutionary Algorithm.- 2.3 Network Design Techniques Using Adapted Genetic Algorithms.- 3. Design Representation Issues.- 3.1 Adaptive Techniques for Evolutionary Topological Optimum Design.- 3.2 Representation in Architectural Design Tools.- 3.3 Fitting of Constrained Feature Models to Poor 3D Data.- 3.4 Exploring Component-based Representations — The Secret of Creativity by Evolution?.- 4. Manufacturing Applications.- 4.1 Evolutionary Design of Facilities Considering Production Uncertainty.- 4.2 A Fuzzy Clustering Evolution Strategy and its Application to Optimisation of Robot Manipulator Movement.- 4.3 An Industry-based Development of the Learning Classifier System Technique.- 4.4 A Genetic Programming-based Hierarchical Clustering Procedure for the Solution of the Cell-formation Problem.- 5. Multi-objective Satisfaction.- 5.1 Multi-objective Evolutionary Optimization: Past, Present and Future.- 5.2 City Planning with a Multiobjective Genetic Algorithm and a Pareto Set Scanner.- 5.3 Designer’s Preferences and Multi-objective PreliminaryDesign Processes.- 6. Algorithm Comparison and Development.- 6.1 Improving the Robustness of COGA: The Dynamic Adaptive Filter.- 6.2 Efficient Evolutionary Algorithms for Searching Robust Solutions.- 6.3 A Comparison of Semi-deterministic and Stochastic Search Techniques.- 6.4 A Multi-population Approach to Dynamic Optimization Problems.- 6.5 Short Term Memory in Genetic Programming.- 7. Neural Nets and Hybrid Systems.- 7.1 Application of Bayesian Neural Networks to Non-linear Function Modelling for Powder Metals.- 7.2 Development of an Iterative Neural Network and Genetic Algorithm Procedure for Shipyard Scheduling.- 7.3 Adaptive Radial Basis Function Emulators for Robust Design.- 7.4 An Evolutionary Neural Network Controller for Intelligent Active Force Control.- 7.5 Quality Inspection of Veneer Using Soft-computing Methods.- Author Index.

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