Adaptive Computing in Design and Manufacture V

ISBN-13: 9781852336059 / Angielski / Miękka / 2002 / 393 str.

Torsten Halskov Soderstrom; I. C. Parmee; I. C. Parmee

Opis

The Adaptive Computing in Design and Manufacture Conference series is now in its tenth year and has become a well-established, application-oriented meeting recognised by several UK Engineering Institutions and the International Society of Genetic and Evolutionary Computing. The main theme of the conference again relates to the integration of evolutionary and adaptive computing technologies with design and manufacturing processes whilst also taking into account complementary advanced computing technologies. Evolutionary and adaptive computing techniques continue to increase their penetration of industrial and commercial practice as their powerful search, exploration and optimisation capabilities become ever more apparent. The last two years have seen a very significant increase in the development of commercial software tools utilising adaptive computing technologies and the emergence of related commercial research and consultancy organisations supporting the introduction of best practice in terms of industrial utilisation. Adaptive Computing in Design and Manufacture V is comprised of selected papers that cover a diverse set of industrial application areas including: engineering design and design environments, manufacturing process design, scheduling and control, electronic circuit design, fault detection. Various aspects of search and optimisation such as multi-objective and constrained optimisation are also investigated in the context of integration with industrial processes. In addition to evolutionary computing techniques, both neural-net and agent-based technologies play a role in a number of contributions. This collection of papers will be of particular interest to both industrial researchers and practitioners in addition to the academic research communities of engineering, operational research and computer science.

Spis treści

Chapter 1 Plenary Papers Pareto Solutions of Multipoint Design of Supersonic Wings Using Evolutionary Algorithms Notes on Design Through Artificial Evolution: Opportunities and Algorithms Testing, Evaluation and Performance of Optimisation and Learning Systems From Evolutionary Computation to Natural Computation Chapter 2 Engineering Design ApplicationsExperiences with Hybrid Evolutionary/Local Optimisation for Process Design The Development of a Grid-based Engineering Design Problem Solving EnvironmentA Hybrid Search Technique for Inverse Transient Analysis in Water Distribution SystemsOptimisation of Thermal Power Plant Designs: A Graph-based Adaptive Search Approach Genetic Algorithm Search for Stent Design Improvements A Multi-objective Optimisation Approach for the Conceptual Design of Frame Structures Multi-Objective Evolutionary Topological Optimum Design Better Surface Intersections by Constrained EvolutionInverse Identification of Boundary Constants for Electronic Packages Using Modified Micro-genetic Algorithm and the Reduced-basis Method Extrinsic Evolution of Finite State Machines Chapter 3 Manufacturing Processes Neural Computing Approach to Shape Change Estimation in Hot Isostatic PressingMulti-criterion Tackling Bottleneck Machines and Exceptional Parts in Cell Formation Using Genetic Algorithms A New Approach to Packing Non-Convex Polygons Using the No Fit Polygon and Meta-Heuristic and Evolutionary Algorithms Chapter 4 System/Process Control Evolutionary Multi-criteria Optimisation for Improved Design of Optimal Control Systems Explorations in Fuzzy Classifier System Architectures Evolving Temporal Rules with the Delayed Action Classifier System - Analysis and New Results Adaptive Image Segmentation Based on Visual Interactive Feedback LearningChapter 5 Strategy/Algorithm DevelopmentAdapting Problem Specifications and Design Solutions Using Co-evolution Handling Constraints in Genetic Algorithms Using Dominance-based TournamentsThe Optimisation of Multi-variate Robust Design CriteriaLearning from Experience: Case Injected Genetic Algorithm Design of Combinational Logic Circuits Constrained Optimisation with the Fuzzy Clustering Evolution StrategyConstrained Optimisation Using an Evolutionary Programming-based Cultural Algorithm A Data Mining Tool Using an Intelligent Processing System with a Clustering Application Chapter 6 Multiple Objectives, Preferences and Agent-Support Full Elite Sets for Multi-objective Optimisation Agent-based Support within an Interactive Evolutionary Design SystemA Multi-agent Architecture for Business Process Management Adapts to Unreliable Performance Real-time Co-ordinated Scheduling Using a Genetic Algorithm