Applications of Evolutionary Computation

Evolutionary computation (EC) techniques are e?cient, nature-inspired me- ods based on the principles of natural evolution and genetics. Due to their - ciency and simple underlying principles, these methods can be used for a diverse rangeofactivitiesincludingproblemsolving,optimization,machinelearningand pattern recognition. A large and continuously increasing number of researchers and professionals make use of EC techniques in various application domains. This volume presents a careful selection of relevant EC examples combined with a thorough examination of the techniques used in EC. The papers in the volume illustrate the current state of the art in the application of EC and should help and inspire researchers and professionals to develop e?cient EC methods for design and problem solving. All papers in this book were presented during EvoApplications 2010, which included a range of events on application-oriented aspects of EC. Since 1998, EvoApplications formerly known as EvoWorkshops has provided a unique opportunity for EC researchers to meet and discuss application aspects of EC and has been an important link between EC research and its application in a variety of domains. During these 12 years, new events have arisen, some have disappeared,whileothershavematuredtobecomeconferencesoftheirown,such as EuroGP in 2000, EvoCOP in 2004, and EvoBIO in 2007. And from this year, EvoApplications has become a conference as well.

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Autorentext
Anthony Brabazon [B. Comm (UCD), DPA (UCD), Dip Stats (Dub), MS (Statistics) (Stanford), MS (Operations Research) (Stanford), MBA (Heriot-Watt), DBA (Kingston), FCA, ACMA] lectures at University College Dublin. His research interests include mathematical decision models, evolutionary computation, and the application of computational intelligence to the domain of finance. He has published in excess of 100 papers in journals, conferences and professional publications, and has been a member of the programme committee at both EuroGP and GECCO conferences, as well as acting as reviewer for several journals. He has also acted as consultant to a wide range of public and private companies in several countries. He currently serves as a member of the CCAB (Ireland) Consultative Committee on Accounting Standards, and is a former Secretary and Treasurer of the Irish Accounting and Finance Association. Prior to joining UCD, he worked in the banking sector, and for KPMG.
Michael O'Neill [BSc. (UCD), PhD (UL)] is a lecturer in the Department of Computer Science and Information Systems at the University of Limerick. He has over 70 publications on biologically inspired algorithms (BIAs). He coauthored the Springer title "Grammatical Evolution -- Evolutionary Automatic Programming in an Arbitrary Language", Genetic Programming Series, 2003, 160 pp., ISBN 1-4020-7444-1. He is one of the two original developers of the Grammatical Evolution algorithm, research that spawned an annual invited tutorial at the largest evolutionary computation conference and an international workshop, and is also on a number of relevant organising committees (e.g., GECCO 2005). Michael is a regular reviewer for the leading evolutionary computation (EC) journals, namely IEEE Trans. on Evolutionary Computation, MIT Press's Evolutionary Computation, and Springer's Genetic Programming and Evolvable Hardware journal.

Inhalt
EvoCOMNET Contributions.- Detection of DDoS Attacks via an Artificial Immune System-Inspired Multiobjective Evolutionary Algorithm.- Performance Evaluation of an Artificial Neural Network-Based Adaptive Antenna Array System.- Automatic Parameter Tuning with Metaheuristics of the AODV Routing Protocol for Vehicular Ad-Hoc Networks.- WiMAX Network Planning Using Adaptive-Population-Size Genetic Algorithm.- Markov Chain Models for Genetic Algorithm Based Topology Control in MANETs.- Particle Swarm Optimization for Coverage Maximization and Energy Conservation in Wireless Sensor Networks.- Efficient Load Balancing for a Resilient Packet Ring Using Artificial Bee Colony.- TCP Modification Robust to Packet Reordering in Ant Routing Networks.- Solving the Physical Impairment Aware Routing and Wavelength Assignment Problem in Optical WDM Networks Using a Tabu Search Based Hyper-Heuristic Approach.- A Generalized, Location-Based Model of Connections in Ad-Hoc Networks Improving the Performance of Ant Routing.- Using Code Bloat to Obfuscate Evolved Network Traffic.- ABC Supported Handoff Decision Scheme Based on Population Migration.- EvoENVIRONMENT Contributions.- A Hyper-Heuristic Approach for the Unit Commitment Problem.- Application of Genetic Programming Classification in an Industrial Process Resulting in Greenhouse Gas Emission Reductions.- Influence of Topology and Payload on CO2 Optimised Vehicle Routing.- Start-Up Optimisation of a Combined Cycle Power Plant with Multiobjective Evolutionary Algorithms.- EvoFIN Contributions.- A Study of Nature-Inspired Methods for Financial Trend Reversal Detection.- Outperforming Buy-and-Hold with Evolved Technical Trading Rules: Daily, Weekly and Monthly Trading.- Evolutionary Multi-stage Financial Scenario Tree Generation.- EvolvingDynamic Trade Execution Strategies Using Grammatical Evolution.- Modesty Is the Best Policy: Automatic Discovery of Viable Forecasting Goals in Financial Data.- Threshold Recurrent Reinforcement Learning Model for Automated Trading.- Active Portfolio Management from a Fuzzy Multi-objective Programming Perspective.- Evolutionary Monte Carlo Based Techniques for First Passage Time Problems in Credit Risk and Other Applications in Finance.- Calibrating the Heston Model with Differential Evolution.- Evolving Trading Rule-Based Policies.- EvoMUSART Contributions.- Evolving Artistic Styles through Visual Dialogues.- Graph-Based Evolution of Visual Languages.- Refinement Techniques for Animated Evolutionary Photomosaics Using Limited Tile Collections.- Generative Art and Evolutionary Refinement.- Aesthetic Learning in an Interactive Evolutionary Art System.- Comparing Aesthetic Measures for Evolutionary Art.- The Problem with Evolutionary Art Is ....- Learning to Dance through Interactive Evolution.- Jive: A Generative, Interactive, Virtual, Evolutionary Music System.- A Neural Network for Bass Functional Harmonization.- Combining Musical Constraints with Markov Transition Probabilities to Improve the Generation of Creative Musical Structures.- Dynamic Musical Orchestration Using Genetic Algorithms and a Spectro-Temporal Description of Musical Instruments.- Evolutionary Sound Synthesis: Rendering Spectrograms from Cellular Automata Histograms.- Sound Agents.- From Evolutionary Composition to Robotic Sonification.- Musical Composer Identification through Probabilistic and Feedforward Neural Networks.- EvoTRANSLOG Contributions.- Using an Evolutionary Algorithm to Discover Low CO2 Tours within a Travelling Salesman Problem.- A Genetic Algorithm for the Traveling Salesman Problemwith Pickup and Delivery Using Depot Removal and Insertion Moves.- Fast Approximation Heuristics for Multi-Objective Vehicle Routing Problems.- Particle Swarm Optimization and an Agent-Based Algorithm for a Problem of Staff Scheduling.- A Math-Heuristic for the Multi-Level Capacitated Lot Sizing Problem with Carryover.