Adaptive Computing in Design and Manufacture VI

1. Front Matter

   Pages i-xi

   PDF

2. Plenary Papers

   1. Front Matter

      Pages 1-1

      PDF

   2. The Everyday Engineering of Organizational and Engineering Innovation

      • David E. Goldberg

      Pages 3-12

   3. Mixing Maths with Cases

      • I. F. C. Smith

      Pages 13-21

3. Engineering Design Applications

   1. Front Matter

      Pages 23-23

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   2. Morphogenic Evolutionary Design: Cellular Automata Representations in Topological Structural Design

      • Rafal Kicinger, Tomasz Arciszewski, Kenneth De Jong

      Pages 25-38

   3. Design search and optimisation using radial basis functions with regression capabilities

      • A. J. Keane

      Pages 39-49

   4. Genetic Programming within Civil Engineering

      • David Shaw, John Miles, Alex Gray

      Pages 51-61

   5. Enhancing Automated Process Design with Cognitive Agents, Distributed Software Components and Web Repositories

      • Iain D. Stalker, Eric S. Fraga

      Pages 63-74

   6. Robust Solutions in Engineering Design: stochastic simulation versus DACE

      • R. A. Bates, H. P. Wynn

      Pages 75-86

   7. Adaptive Search for Optimum in a Problem of Oil Stabilization Process Design

      • A. Žilinskas, E. S. Fraga, A. Mackutė, A. Varoneckas

      Pages 87-98

   8. Application of Artificial Neural Networks In Differential Pulse Code Modulation Scheme

      • H. B. Bahar

      Pages 99-109

4. Manufacturing Processes

   1. Front Matter

      Pages 111-111

      PDF

   2. Job Shop Scheduling using the Clonal Selection Principle

      • Carlos A. Coello Coello, Daniel Cortés Rivera, Nareli Cruz Cortés

      Pages 113-124

   3. Genetic Optimisation of Machine Tool Paths

      • M. K. A. Mohd Ariffin, N. D. Sims, K. Worden

      Pages 125-135

   4. Automating the Analysis of Wafer Data Using Adaptive Resonance Theory Networks

      • Emilio Miguelañez, Ali M S Zalzala, Paul Tabor

      Pages 137-148

   5. Job Shop Scheduling using Multi-Agent Systems

      • A. M. Booth

      Pages 149-160

   6. Tool Wear Prediction Approach for Turning Operations Based on General Regression Neural Network (GRNN) Technique

      • E. A. Almeshaiei, S. E. Oraby, M. A. Mahmoud

      Pages 161-172

   7. An Efficient Genetic Algorithm to Solve the Manufacturing Cell Formation Problem

      • W. Rojas, M. Solar, M. Chacón, J. Ferland

      Pages 173-183

   8. Evolutionary Simulated Annealing Algorithms for Uncapacitated Facility Location Problems

      • Vecihi Yigit, M. Emin Aydin, Orhan Turkbey

      Pages 185-194

The Adaptive Computing in Design and Manufacture conference series has become a well-established, largely application-oriented meeting recognised by several UK Engineering Institutions and the International Society of Genetic and Evolutionary Computing. The main theme of the series 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 awareness of their powerful search, exploration and optimisation capabilities becomes ever more prevalent, and increasing desk-top computational capability renders stochastic population-based search a far more viable proposition. There has been a significant increase in the development and integration 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. The book is comprised of selected papers that cover a diverse set of industrial application areas including engineering design and design environments and manufacturing process design, scheduling and control. Various aspects of search, exploration and optimisation are investigated in the context of integration with industrial processes including multi-objective and constraint satisfaction, development and utilization of meta-models, algorithm and strategy development and human-centric evolutionary approaches. The role of agent-based and neural net technologies in terms of supporting search processes and providing an alternative simulation environment is also explored. This collection of papers will be of particular interest to both industrial researchers and practitioners in addition to the academic research communities across engineering, operational research and computer science.

• Adaptive Computing
• Constraint Satisfaction
• Evolutionary computation
• Performance
• Service-oriented Computing
• Simulation
• civil engineering
• computational intelligence
• design
• engineering design
• evolutionary algorithm
• genetic programming
• machine learning
• manufacturing
• organization

• CEMS, University of the West of England, Bristol, UK

  I. C. Parmee

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