Evolutionary Computing

Some combinatorial landscapes on which a Genetic Algorithm outperforms other Stochastic iterative methods.- Maximum entropy analysis of genetic algorithm operators.- The ant colony metaphor for searching continuous design spaces.- Broadcast based fitness sharing GA for conflict resolution among autonomous robots.- An adaptive poly-parental recombination strategy.- Neighbourhood seeding to reduce problem modality.- Specialised recombinative operators for timetabling problems.- The use of local search suggestion lists for improving the solution of timetable problems with evolutionary algorithms.- Comparing genetic algorithms, simulated annealing, and stochastic hillclimbing on timetabling problems.- Evolutionary learning in computational ecologies: An application to adaptive distributed routing in communication networks.- The radio link frequency assignment problem: A case study using genetic algorithms.- Scheduling planned maintenance of the national grid.- Genetic operators and constraint handling for pipe network optimization.- A multi-objective approach to constrained optimisation of gas supply networks: The COMOGA method.- Ternary decision diagram optimisation of Reed-Muller logic functions using a genetic algorithm for variable and simplification rule ordering.- An evolutionary algorithm for parametric array signal processing.- Constraints on task and search complexity in GA+NN models of learning and adaptive behaviour.- Load balancing application of the genetic algorithm in a nonstationary environment.- Exploring some commercial applications of genetic programming.