Theoretical Aspects of Evolutionary Computing

I: Tutorials.- to Evolutionary Computing in Design Search and Optimisation.- Evolutionary Algorithms and Constraint Satisfaction: Definitions, Survey, Methodology, and Research Directions.- The Dynamical Systems Model of the Simple Genetic Algorithm.- Modelling Genetic Algorithm Dynamics.- Statistical Mechanics Theory of Genetic Algorithms.- Theory of Evolution Strategies - A Tutorial.- Evolutionary Algorithms: From Recombination to Search Distributions.- Properties of Fitness Functions and Search Landscapes.- II: Technical Papers.- A Solvable Model of a Hard Optimisation Problem.- Bimodal Performance Profile of Evolutionary Search and the Effects of Crossover.- Evolution Strategies in Noisy Environments - A Survey of Existing Work.- Cyclic Attractors and Quasispecies Adaptability.- Genetic Algorithms in Time-Dependent Environments.- Statistical Machine Learning and Combinatorial Optimization.- Multi-Parent Scanning Crossover and Genetic Drift.- Harmonic Recombination for Evolutionary Computation.- How to Detect all Maxima of a Function.- On Classifications of Fitness Functions.- Genetic Search on Highly Symmetric Solution Spaces: Preliminary Results.- Structure Optimization and Isomorphisms.- Detecting Spin-Flip Symmetry in Optimization Problems.- Asymptotic Results for Genetic Algorithms with Applications to Nonlinear Estimation.