Gives the reader a complete overview of the latest discussions in the application of genetic algorithms to solve engineering problems

Real-world applications engage the reader with the complexities of the various genetic algorithms that are described

With the accompanying software, the reader has the opportunity to use an interactive genetic algorithms demonstration programme

1. Introduction, Background and Biological Inspiration.- 1.1 Biological Background.- 1.2 Conventional Genetic Algorithm.- 1.3 Theory and Hypothesis.- 1.4 A Simple Example.- 2. Modifications to Genetic Algorithms.- 2.1 Chromosome Representation.- 2.2 Objective and Fitness Functions.- 2.3 Selection Methods.- 2.4 Genetic Operations.- 2.5 Replacement Scheme.- 2.6 A Game of Genetic Creatures.- 2.7 Chromosome Representation.- 2.8 Fitness Function.- 2.9 Genetic Operation.- 2.10 Demo and Run.- 3. Intrinsic Characteristics.- 3.1 Parallel Genetic Algorithm.- 3.2 Multiple Objective.- 3.3 Robustness.- 3.4 Multimodal.- 3.5 Constraints.- 4. Hierarchical Genetic Algorithm.- 4.1 Biological Inspiration.- 4.2 Hierarchical Chromosome Formulation.- 4.3 Genetic Operations.- 4.4 Multiple Objective Approach.- 5. Genetic Algorithms in Filtering.- 5.1 Digital IIR Filter Design.- 5.2 Time Delay Estimation.- 5.3 Active Noise Control.- 6. Genetic Algorithms in H-infinity Control.- 6.1 A Mixed Optimization Design Approach.- 7. Hierarchical Genetic Algorithms in Computational Intelligence.- 7.1 Neural Networks.- 7.2 Fuzzy Logic.- 8. Genetic Algorithms in Speech Recognition Systems.- 8.1 Background of Speech Recognition Systems.- 8.2 Block Diagram of a Speech Recognition System.- 8.3 Dynamic Time Warping.- 8.4 Genetic Time Warping Algorithm (GTW).- 8.5 Hidden Markov Model using Genetic Algorithms.- 8.6 A Multiprocessor System for Parallel Genetic Algorithms.- 8.7 Global GA for Parallel GA-DTW and PGA-HMM.- 8.8 Summary.- 9. Genetic Algorithms in Production Planning and Scheduling Problems.- 9.1 Background of Manufacturing Systems.- 9.2 ETPSP Scheme.- 9.3 Chromosome Configuration.- 9.4 GA Application for ETPSP.- 9.5 Concluding Remarks.- 10. Genetic Algorithms in Communication Systems.- 10.1 Virtual Path Design in ATM.- 10.2 Mesh Communication Network Design.- 10.3 Wireles Local Area Network Design.- Appendix A.- Appendix B.- Appendix C.- Appendix D.- Appendix E.- Appendix F.- References.