Real-World Applications of Evolutionary Computing

1. Front Matter

   Pages I-XII

   PDF

2. EvoIASP Talks

   1. Special Purpose Image Convolution with Evolvable Hardware

      • Joe Dumoulin, James A. Foster, James F. Frenzel, Steve McGrew

      Pages 1-11

   2. Stereoscopic Vision for a Humanoid Robot Using Genetic Programming

      • Christopher T. M. Graae, Peter Nordin, Mats Nordahl

      Pages 12-21

   3. A Faster Genetic Clustering Algorithm

      • L Meng, Q H Wu, Z Z Yong

      Pages 22-33

   4. Scene Interpretation using Semantic Nets and Evolutionary Computation

      • D. Prabhu, B. P. Buckles, F. E. Petry

      Pages 34-43

   5. Evolutionary Wavelet Bases in Signal Spaces

      • Adelino R. Ferreira da Silva

      Pages 44-53

3. EvoIASP Posters

   1. Finding Golf Courses: The Ultra High Tech Approach

      • Neal R. Harvey, Simon Perkins, Steven P. Brumby, James Theiler, Reid B. Porter, A. Cody Young et al.

      Pages 54-64

   2. Sound Localization for a Humanoid Robot by Means of Genetic Programming

      • Rikard Karlsson, Peter Nordin, Mats Nordahl

      Pages 65-76

   3. On the Scalability of Genetic Algorithms to Very Large-Scale Feature Selection

      • Andreas Moser, M. Narasimha Murty

      Pages 77-86

   4. Combining Evolutionary, Connectionist, and Fuzzy Classification Algorithms for Shape Analysis

      • Paul L. Rosin, Henry O. Nyongesa

      Pages 87-96

   5. Experimental Determination of Drosophila Embryonic Coordinates by Genetic Algorithms, the Simplex Method, and Their Hybrid

      • Alexander V. Spirov, Dmitry L. Timakin, John Reinitz, David Kosman

      Pages 97-106

4. EvoSCONDI Papers

   1. A Genetic Algorithm with Local Search for Solving Job Problems

      • L W Cai, Q H Wu, Z Z Yong

      Pages 107-116

   2. Distributed Learning Control of Traffic Signals

      • Y. J. Cao, N. Ireson, L. Bull, R. Miles

      Pages 117-126

   3. Time Series Prediction by Growing Lateral Delay Neural Networks

      • Lipton Chan, Yun Li

      Pages 127-138

   4. Trajectory Controller Network and Its Design Automation through Evolutionary Computing

      • Gregory Chong, Yun Li

      Pages 139-146

   5. Evolutionary Computation and Nonlinear Programming in Multi-model-robust Control Design

      • Dorothea Kolossa, Georg Grübel

      Pages 147-157

   6. Benchmarking Cost-Assignment Schemes for Multi-objective Evolutionary Algorithms

      • Konstantinos Koukoulakis, Yun Li

      Pages 158-167

   7. Automatic Synthesis of Both the Topology and Parameters for a Controller for a Three-Lag Plant with a Five-Second Delay Using Genetic Programming

      • John R. Koza, Martin A. Keane, Jessen Yu, William Mydlowec, Forrest H Bennett III

      Pages 168-177

   8. Automatic Design of Multivariable QFT Control System via Evolutionary Computation

      • K. C. Tan, T. H. Lee, E. F. Khor

      Pages 178-194

   9. Development of Power Transformer Thermal Models for Oil Temperature Prediction

      • W H Tang, H Zeng, K I Nuttall, Z Richardson, E Simonson, Q H Wu

      Pages 195-204

The increasingly active eld of Evolutionary Computation (EC) provides val- ble tools, inspired by the theory of natural selection and genetic inheritance, to problem solving, machine learning, and optimization in many real-world app- cations. Despite some early intuitions about EC, that can be dated back to the - vention of computers, and a better formal de nition of EC, made in the 1960s, the quest for real-world applications of EC only began in the late 1980s. The dramatic increase in computer performances in the last decade of the 20th c- tury gave rise to a positive feedback process: EC techniques became more and more applicable, stimulating the growth of interest in their study, and allowing, in turn, new powerful EC paradigms to be devised. In parallel with new theoretical results, the number of elds to which EC is being applied is increasing day by day, along with the complexity of applications and application domains. In particular, industrially relevant elds, such as signal and image processing, computer vision, pattern recognition, industrial control, telecommunication, scheduling and timetabling, and aerospace engineering are employing EC techniques to solve complex real-world problems.

• Aeronautics
• Ant algorithm
• Control Telecommunications
• Evolutionary Algorithms
• Fuzzy
• Genetic Algorithms
• Robotics
• Scheduling
• algorithms
• architecture
• automation
• construction
• genetic programming
• modeling
• topology
• algorithm analysis and problem complexity
• complexity

• Department of Computer Engineering, University of Parma, Parma, Italy

  Stefano Cagnoni

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