Parmee | Evolutionary Design and Manufacture | Buch | 978-1-85233-300-3 | sack.de

Buch, Englisch, 372 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 581 g

Parmee

Evolutionary Design and Manufacture

Selected Papers from ACDM ¿00
Softcover Nachdruck of the original 1. Auflage 2000
ISBN: 978-1-85233-300-3
Verlag: Springer

Selected Papers from ACDM ¿00

Buch, Englisch, 372 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 581 g

ISBN: 978-1-85233-300-3
Verlag: Springer


The fourth evolutionary/adaptive computing conference at the University of Plymouth again explores the utility of various evolutionary/adaptive search algorithms and complementary computational intelligence techniques within design and manufacturing. The content of the following chapters represents a selection of the diverse set of papers presented at the conference that relate to both engineering design and also to more general design areas. This expansion has been the result of a conscious effort to recognise generic problem areas and complementary research across a wide range of design and manufacture activity. There has been a major increase in both research into and utilisation of evolutionary and adaptive systems within the last two years. This is reflected in the establishment of major annual joint US genetic and evolutionary computing conferences and the introduction of a large number of events relating to the application of these technologies in specific fields. The Plymouth conference remains a long-standing. event both as ACDM and as the earlier ACEDC series. The conference maintains its policy of single stream presentation and associated poster and demonstrator sessions. The event retains the support of several UK Engineering Institutions and is now recognised by the International Society for Genetic and Evolutionary Computation as a mainstream event. It continues to attract an international audience of leading researchers and practitioners in the field.

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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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