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This volume presents the state of art of research on theory and applications in the field of Evolutionary Computation. It contains contributions of established scientists of the field and maintains a balance of theory and applications. It will be useful for researchers, scientists, professionals, teachers and students interested in the the field; there are non-competitive books.
State of the art of theory and applications in Evolutionary Algorithms Contributions by established researchers in the field Well-balanced between theory and applications Includes supplementary material: sn.pub/extras
Auteur
Amitav Ghosh, geboren 1965, verbrachte seine Kindheit in Dhaka, Colombo, und in seiner Geburtsstadt Kalkutta. Er studierte Geschichte in Neu-Delhi und war bereits während seines Studiums Mitarbeiter verschiedener Zeitungen. Nach seiner Promotion in Oxford unterrichtete er an den Universitäten von Neu-Delhi, Calcutta, Virginia und New York. Ghosh ist Autor mehrerer preisgekrönter Romane und Sachbücher. Heute lebt Amitav Ghosh mit seiner Frau und seinen Kindern in New York.
Contenu
I.- Smoothness, Ruggedness and Neutrality of Fitness Landscapes: from Theory to Application.- Fast Evolutionary Algorithms.- Visualizing Evolutionary Computation.- New Schemes of Biologically Inspired Evolutionary Computation.- On the Design of Problem-specific Evolutionary Algorithms.- Multiparent Recombination in Evolutionary Computing.- TCG-2: A Test-case Generator for Non-linear Parameter Optimisation Techniques.- A Real-coded Genetic Algorithm Using the Unimodal Normal Distribution Crossover.- Designing Evolutionary Algorithms for Dynamic Optimization Problems.- Multi-objective Evolutionary Algorithms: Introducing Bias Among Pareto-optimal Solutions.- Gene Expression and Scalable Genetic Search.- Solving Permutation Problems with the Ordering Messy Genetic Algorithm.- Effects of Adding Perturbations to Phenotypic Parameters in Genetic Algorithms for Searching Robust Solutions.- Evolution of Strategies for Resource Protection Problems.- A Unified Bayesian Framework for EvolutionaryLearning and Optimization.- Designed Sampling with Crossover Operators.- Evolutionary Computation for Evolutionary Theory.- Computational Embryology: Past, Present and Future.- An Evolutionary Approach to Synthetic Biology: Zen in the Art of Creating Life.- Scatter Search.- The Ant Colony Optimization Paradigm for Combinatorial Optimization.- Evolving Coordinated Agents.- Exploring the Predictable.- II.- Approaches to Combining Local and Evolutionary Search for Training Neural Networks: A Review and Some New Results.- Evolving Analog Circuits by Variable Length Chromosomes.- Human-competitive Applications of Genetic Programming.- Evolutionary Algorithms for the Physical Design of VLSI Circuits.- From Theory to Practice: An Evolutionary Algorithm for the Antenna Placement Problem.- Routing Optimization in Corporate Networks by Evolutionary Algorithms.- Genetic Algorithms and Timetabling.- Machine Learning by Schedule Decomposition Prospects for an Integration of AI and OR Techniquesfor Job Shop Scheduling.- Scheduling of Bus Drivers' Service by a Genetic Algorithm.- A Survey of Evolutionary Algorithms for Data Mining and Knowledge Discovery.- Data Mining from Clinical Data Using Interactive Evolutionary Computation.- Learning-integrated Interactive Image Segmentation.- An Immunogenetic Approach in Chemical Spectrum Recognition.- Application of Evolutionary Computation to Protein Folding.- Evolutionary Generation of Regrasping Motion.- Recent Trends in Learning Classifier Systems Research.- Better than Samuel: Evolving a Nearly Expert Checkers Player.