The term evolutionary computing (EC) refers to the study of the foundations and applications of certain heuristic techniques based on the principles of natural evolution, and thus the aim when designing evolutionary algorithms (EAs) is to mimic some of the processes taking place in natural evolution.
Many researchers around the world have been developing EC methodologies for designing intelligent decision-making systems for a variety of real-world problems. This book provides a collection of 40 articles, written by leading experts in the field, containing new material on both the theoretical aspects of EC and demonstrating its usefulness in various kinds of large-scale real-world problems. Of the articles contributed, 23 articles deal with various theoretical aspects of EC and 17 demonstrate successful applications of EC methodologies.
Author(s): Ashish Ghosh, Shigeyoshi Tsutsui (eds.)
Series: Natural Computing Series
Publisher: Springer
Year: 2003
Language: English
Pages: 1000
Tags: Theory of Computation; Computer Appl. in Life Sciences; Artificial Intelligence (incl. Robotics); Computation by Abstract Devices; Algorithm Analysis and Problem Complexity
Front Matter....Pages I-XVI
Front Matter....Pages 1-1
Smoothness, Ruggedness and Neutrality of Fitness Landscapes: from Theory to Application....Pages 3-44
Fast Evolutionary Algorithms....Pages 45-94
Visualizing Evolutionary Computation....Pages 95-116
New Schemes of Biologically Inspired Evolutionary Computation....Pages 117-151
On the Design of Problem-specific Evolutionary Algorithms....Pages 153-173
Multiparent Recombination in Evolutionary Computing....Pages 175-192
TCG-2 : A Test-Case Generator for Non-linear Parameter Optimisation Techniques....Pages 193-212
A Real-coded Genetic Algorithm using the Unimodal Normal Distribution Crossover....Pages 213-237
Designing Evolutionary Algorithms for Dynamic Optimization Problems....Pages 239-262
Multi-objective Evolutionary Algorithms: Introducing Bias Among Pareto-optimal Solutions....Pages 263-292
Gene Expression and Scalable Genetic Search....Pages 293-319
Solving Permutation Problems with the Ordering Messy Genetic Algorithm....Pages 321-350
Effects of Adding Perturbations to Phenotypic Parameters in Genetic Algorithms for Searching Robust Solutions....Pages 351-365
Evolution of Strategies for Resource Protection Problems....Pages 367-392
A Unified Bayesian Framework for Evolutionary Learning and Optimization....Pages 393-412
Designed Sampling with Crossover Operators....Pages 413-439
Evolutionary Computation for Evolutionary Theory....Pages 441-460
Computational Embryology: Past, Present and Future....Pages 461-477
An Evolutionary Approach to Synthetic Biology: Zen in the Art of Creating Life....Pages 479-517
Scatter Search....Pages 519-537
Front Matter....Pages 1-1
The Ant Colony Optimization Paradigm for Combinatorial Optimization....Pages 539-557
Evolving Coordinated Agents....Pages 559-577
Exploring the Predictable....Pages 579-612
Front Matter....Pages 613-613
Approaches to Combining Local and Evolutionary Search for Training Neural Networks: A Review and Some New Results....Pages 615-641
Evolving Analog Circuits by Variable Length Chromosomes....Pages 643-662
Human-competitive Applications of Genetic Programming....Pages 663-682
Evolutionary Algorithms for the Physical Design of VLSI Circuits....Pages 683-711
From Theory to Practice: An Evolutionary Algorithm for the Antenna Placement Problem....Pages 713-737
Routing Optimization in Corporate Networks by Evolutionary Algorithms....Pages 739-753
Genetic Algorithms and Timetabling....Pages 755-771
Machine Learning by Schedule Decomposition — Prospects for an Integration of AI and OR Techniques for Job Shop Scheduling....Pages 773-798
Scheduling of Bus Drivers’ Service by a Genetic Algorithm....Pages 799-817
A Survey of Evolutionary Algorithms for Data Mining and Knowledge Discovery....Pages 819-845
Data Mining from Clinical Data using Interactive Evolutionary Computation....Pages 847-861
Learning-integrated Interactive Image Segmentation....Pages 863-895
An Immunogenetic Approach in Chemical Spectrum Recognition....Pages 897-914
Application of Evolutionary Computation to Protein Folding....Pages 915-940
Evolutionary Generation of Regrasping Motion....Pages 941-954
Recent Trends in Learning Classifier Systems Research....Pages 955-988
Beyond Samuel: Evolving a Nearly Expert Checkers Player....Pages 989-1004
Back Matter....Pages 1005-1007
