Download Applications of Evolutionary Computation: EvoApplications 2010: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoMUSART, and EvoTRANSLOG, Istanbul, Turkey, April 7-9, 2010, Proceedings, Part II PDF

Table of Contents

                            Cover
Front matter
1. Detection of DDoS Attacks via an Artificial Immune System-Inspired Multiobjective Evolutionary Algorithm
	Detection of DDoS Attacks via an Artificial Immune System-Inspired Multiobjective Evolutionary Algorithm
		Introduction
		Background
			Intrusion Detection Systems (IDS)
			Distributed Denial of Service Attack (DDoS)
			Datasets
		JREMISA (Java REtrovirus-inspired Multiobjective Immune System Algorithm)
			Representation of Antigens and Antibodies
			Immune Algorithm
		Proposed Improvements on jREMISA
		Experiments
			Test Designs
			Results
		Conclusion
		References
2. Performance Evaluation of an Artificial Neural Network-Based Adaptive Antenna Array System
	Performance Evaluation of an Artificial Neural Network-Based Adaptive Antenna Array System
		Introduction
		Principle AAA System Configuration
		The Smart Neural AAA System Model
			Data Processing Unit
			The ANNP Unit
		Discussion of Simulation Results
		Conclusions
		References
3. Automatic Parameter Tuning with Metaheuristics of the AODV Routing Protocol for Vehicular Ad-Hoc Networks
	Automatic Parameter Tuning with Metaheuristics of the AODV Routing Protocol for Vehicular Ad-Hoc Networks
		Introduction
		AODV Parameter Tuning
		Optimization Strategy
		VANET Scenario and Mobility Models
		Experiments
			Parameter Settings of the Optimization Algorithms
			Simulation Results and Comparisons
			QoS Analysis
		Conclusions
4. WiMAX Network Planning Using Adaptive-Population-Size Genetic Algorithm
	WiMAX Network Planning Using Adaptive-Population-Size Genetic Algorithm
		Introduction
		Background
			Problem Formulation
			Related Works
		Adaptive-Population-Size Genetic Algorithm
			Individual Representation
			Evolution Framework
			Adaptive Population Size Adjustment
			Evolutionary Operations
		Simulation
			Network Layouts and Algorithm Configuration
			Results
		Concluding Remarks and Future Research
5. Markov Chain Models for Genetic Algorithm Based Topology Control in MANETs
	Markov Chain Models for Genetic Algorithm Based Topology Control in MANETs
		Introduction
		Our Forced-Based GA
		Ergodic Homogeneous Finite Markov Chains
			Convergence of Ergodic Homogeneous Finite Markov Chain
		Simulation Experiments of Convergence for Our Forced-Based GA
		Conclusion and Future Work
6. Particle Swarm Optimization for Coverage Maximization and Energy Conservation in Wireless Sensor Networks
	Particle Swarm Optimization for Coverage Maximization and Energy Conservation in Wireless Sensor Networks
		Introduction
		Particle Swarm Optimization
		PSO for WSN Coverage Optimization
			Particle Encoding
			Fitness Function
		Results and Discussion
		Conclusion
		References
7. Efficient Load Balancing for a Resilient Packet Ring Using Artificial Bee Colony
	Efficient Load Balancing for a Resilient Packet Ring Using Artificial Bee Colony
		Introduction
		Problem Definition
		Proposed ABC
		Results
		Conclusions
		References
8. TCP Modification Robust to Packet Reordering in Ant Routing Networks
	TCP Modification Robust to Packet Reordering in Ant Routing Networks
		Introduction
			Swarm Intelligence and Ant Routing
			The TCP Protocol
		The TCP Modification
			Packet Delay Modeling
			Delay Model Based TCP
		Experimental Results
			Network without Packet Loss
			Network with Packet Loss
		Conclusions
9. Solving the Physical Impairment Aware Routing and Wavelength Assignment Problem in Optical WDM Networks Using a Tabu Search Based Hyper-Heuristic Approach
	Solving the Physical Impairment Aware Routing and Wavelength Assignment Problem in Optical WDM Networks Using a Tabu Search Based Hyper-Heuristic Approach
		Introduction
		Literature Survey and Problem Definition
			Literature Survey
			Routing and Wavelength Assignment Problem
		Solution Approaches
			Hyper-Heuristics
			Proposed Method
		Experimental Design
		Results
		Conclusion and Future Work
10. A Generalized, Location-Based Model of Connections in Ad-Hoc Networks Improving the Performance of Ant Routing
	A Generalized, Location-Based Model of Connections in Ad-Hoc Networks Improving the Performance of Ant Routing
		Introduction
		Related Work
		Generalized Model of Connections
			Ad-hoc network graph - nodes level.
				Ad-hoc network graph - locations level.
		AntHocGeo Algorithm
		Experimental Results
			Connections Stability
			The Overhead
			Overall Performance
		Conclusions
11. Using Code Bloat to Obfuscate Evolved Network Traffic
	Using Code Bloat to Obfuscate Evolved Network Traffic
		Introduction
		Background
			Port Scans
			TCP/IP Packets
			Code Bloat
		Evolutionary Model
			Instruction Set
			Fitness Evaluation
			Evolutionary Model
		Experiments and Results
			Analysis
		Conclusion and Future Work
12. ABC Supported Handoff Decision Scheme Based on Population Migration
	ABC Supported Handoff Decision Scheme Based on Population Migration
		Introduction
		Model Description
			Application Type, QoS Requirement and Its Fuzzy Degree
			Access Network Model and Terminal Model
			Satisfaction Degree and Suitability Degree
			Gaming Analysis and Utility Calculation
			Mathematical Model
		Algorithm Description
			Solution Encoding and Its Attraction Force Function
			Algorithm Procedure
		Simulation Implementation and Performance Evaluation
		Conclusion
		References
13. A Hyper-Heuristic Approach for the Unit Commitment Problem
	A Hyper-Heuristic Approach for the Unit Commitment Problem
		Introduction
		The Unit Commitment Problem
		Hyper-Heuristics
		Related Work on the UCP
		Proposed Approach
		Experiments
			Parameter Settings
			Experimental Results
		Conclusion
		References
14. Application of Genetic Programming Classification in an Industrial Process Resulting in Greenhouse Gas Emission Reductions
	Application of Genetic Programming Classification in an Industrial Process Resulting in Greenhouse Gas Emission Reductions
		Introduction
		Data and Methods
		Experiments and Results
			The CART Model
			GP Evolved Pure Classification Rules (Class-GP)
			GP Evolved Regression Function (Reg-GP)
		Discussion
		Conclusions
15. Influence of Topology and Payload on CO 2  Optimised Vehicle Routing
	Influence of Topology and Payload on CO2 Optimised Vehicle Routing
		Introduction
		Related Work
		CO2 Emission Modelling
		Experimental Approach
		Evidence
		Conclusions
16. Start-Up Optimisation of a Combined Cycle Power Plant with Multiobjective Evolutionary Algorithms
	Start-Up Optimisation of a Combined Cycle Power Plant with Multiobjective Evolutionary Algorithms
		Introduction
		Multiobjective Optimisation
			Multiobjective Evolutionary Algorithms
		Start-Up Optimisation of a Combined Cycle Power Plant
		Experimentations
		Results
			Discussion
		Conclusion and Future Work
17. A Study of Nature-Inspired Methods for Financial Trend Reversal Detection
	A Study of Nature-Inspired Methods for Financial Trend Reversal Detection
		Introduction
		Problem Description
		Detector Set Definition and Nature-Inspired Methodologies
			Particle Swarm Optimization
			Negative Selection
		Experiments and Results
			Discussion
		Conclusion and Future Work
18. Outperforming Buy-and-Hold with Evolved Technical Trading Rules: Daily, Weekly and Monthly Trading
	Outperforming Buy-and-Hold with Evolved Technical Trading Rules: Daily, Weekly and Monthly Trading
		Introduction
		Evolving Robust Trading Rules: The Modified AK/BS Approach
			Overview
			Function and Terminal Sets
			The Fitness Function
			Operators and Initialization
		Experiments
			GP Parameters, Data Periods and Consistency-of Performance Periods
			Results
		Concluding Summary and Discussion
		References
19. Evolutionary Multi-stage Financial Scenario Tree Generation
	Evolutionary Multi-stage Financial Scenario Tree Generation
		Introduction
		Multi-stage Scenario Tree Generation
		Evolutionary Multi-stage Scenario Tree Generation
		Numerical Results
		Conclusion
20. Evolving Dynamic Trade Execution Strategies Using Grammatical Evolution
	Evolving Dynamic Trade Execution Strategies Using Grammatical Evolution
		Introduction
		Background
		Evolving Dynamic Trade Execution Strategies
			Information Indicators
			Grammar of Grammatical Evolution Algorithm
			Performance Evaluation
		Simulating an Artificial Market
		Results
		Conclusions and Future Work
21. Modesty Is the Best Policy: Automatic Discovery of Viable Forecasting Goals in Financial Data
	Modesty Is the Best Policy: Automatic Discovery of Viable Forecasting Goals in Financial Data
		Introduction
		Background
		The Hybrid Forecasting System
			Representation.
			Fitness Evaluation
				Calculating the Predictability for each Genome.
				Calculating Profitability for each Genome.
				Calculating the Dominance Count for each Genome.
			Sexual Operations
			Additional Considerations
		Experimental Setup
			Data preparation
			Comparison Approaches
		Results
		Conclusions
22. Threshold Recurrent Reinforcement Learning Model for Automated Trading
	Threshold Recurrent Reinforcement Learning Model for Automated Trading
		Introduction
		Model Description
			Threshold Recurrent Reinforcement Learning
			Differential Sharpe Ratio for Online Learning
		Experiments
			Setup
			Data
			Results and Discussion
		Conclusion
23. Active Portfolio Management from a Fuzzy Multi-objective Programming Perspective
	Active Portfolio Management from a Fuzzy Multi-objective Programming Perspective
		Introduction
		Index Tracking with Cardinality Constraints
		Nature-Inspired Optimisation Algorithms
		Traditional vs. Fuzzy Enhanced Indexation
		Empirical Study: Actively Reproducing the Dow Jones Industrial Average Index
			Sample Data and Experimental Design
		Discussion - Further Research
24. Evolutionary Monte Carlo Based Techniques for First Passage Time Problems in Credit Risk and Other Applications in Finance
	Evolutionary Monte Carlo Based Techniques for First Passage Time Problems in Credit Risk and Other Applications in Finance
		Introduction
		First Passage Time in Credit Risk Models
		Multivariate Jump-Diffusion Processes and Monte Carlo Simulations
		Density Functions, Default Rates, and Correlated Default
		Conclusion
25. Calibrating the Heston Model with Differential Evolution
	Calibrating the Heston Model with Differential Evolution
		Introduction
		Pricing with the Characteristic Function
			Black–Scholes–Merton
			The Heston Model
			Integration Schemes
		Calibrating the Model Parameters
			Differential Evolution
			Calibrating the Heston Model
		Conclusion
26. Evolving Trading Rule-Based Policies
	Evolving Trading Rule-Based Policies
		Introduction
			Structure of Paper
		Rule-Based Policies
		Grammatical Representation
		Evolution of Trading Policies
			Data Review
			Methodology
		Results
			Example Evolved Policy
		Conclusion and Future Work
27. Evolving Artistic Styles through Visual Dialogues
	Evolving Artistic Styles through Visual Dialogues
敳敲癥搠䁤 㴀 ⨀䁬整䁴潫敮 ⴀ㈀洀
		Introduction
		Background and Motivation
		A Description of I3
			The Top-Level Behavior
			The Generator Component
			The Analyzer Component
		I3 Experience
		Summary and Future Work
28. Graph-Based Evolution of Visual Languages
	Graph-Based Evolution of Visual Languages
		Introduction
		Context Free
		Evolutionary Context Free Art
			Crossover Operator
			Mutation Operators
		Experimentation
			Fitness Functions
			Experimental Results
		Conclusions and Future Work
29. Refinement Techniques for Animated Evolutionary Photomosaics Using Limited Tile Collections
	Refinement Techniques for Animated Evolutionary Photomosaics Using Limited Tile Collections
		Introduction
		Related Work
		Refinement Strategies in Photomosaic Generation
			Colour Adjustment
			Tile Size Variation
			Fitness Evaluation
		Results and Discussion
			Colour Adjustment
			Tile Size Variation
		Conclusions
30. Generative Art and Evolutionary Refinement
	Generative Art and Evolutionary Refinement
		Introduction
		Our Cellular Morphogenesis Evolutionary Art System
		Evolutionary Exploration Using Fitness Functions
		Analysis of the Source Material
		Evolutionary Refinement of the Source Material
		Conclusion
31. Aesthetic Learning in an Interactive Evolutionary Art System
	Aesthetic Learning in an Interactive Evolutionary Art System
		Introduction
		Features for Measuring Aesthetics
			Image Complexity Estimation
			Image Order Estimation
		Experimental Results
			Experimental Setup
				Genetic Programming.
				Mutation Operators.
				Evolutionary and Learning Process.
			Aesthetic Learning
				Accuracy of Prediction.
				Decision Tree.
				Generation Results.
			Validation Study
		Conclusions and Future Work
32. Comparing Aesthetic Measures for Evolutionary Art
	Comparing Aesthetic Measuresfor Evolutionary Art
		Introduction
			Research Question
		Evolutionary Art
			Four Aesthetic Measures
		Arabitat: The Art Habitat
		Experiments
			Results
			Cross Evaluation
		Conclusions
		Future Work
33. The Problem with Evolutionary Art Is ...
	The Problem with Evolutionary Art Is …
		Introduction
		The Problem of Fitness Functions for Evolutionary Art
			Interactive Evolutionary Computing
			Computational Aesthetic Evaluation
			Hybrid Aesthetic Evaluation
			The Future of Aesthetic Evaluation for Evolutionary Art
		The Problem of Genetic Representation and Innovation
			Complexification in Nature and Genetic Representation
		The Problem of Art Theory for Evolutionary Art
			Evolutionary Art Theory and Truth to Process
		References
34. Learning to Dance through Interactive Evolution
	Learning to Dance through Interactive Evolution
		Introduction
		Background
		Approach
			ANN Inputs
			Audio Processing
			ANN Outputs
			ANN Training
		Experiments and Results
			Dancing to MIDI
			Dancing to Raw Audio
		Discussion
		Conclusion
35. Jive: A Generative, Interactive, Virtual, Evolutionary Music System
	Jive: A Generative, Interactive, Virtual, Evolutionary Music System
		Introduction
		Previous Work
		The Basic Jive System
			Generative
			Interactive
			Virtual
			Evolutionary
		Results and Refinements
		Discussion
		Conclusions and Future Work
36. A Neural Network for Bass Functional Harmonization
	A Neural Network for Bass Functional Harmonization
		Introduction
		The Neural Networks
		Training, Validation and Test Results
		Conclusions
37. Combining Musical Constraints with Markov Transition Probabilities to Improve the Generation of Creative Musical Structures
	Combining Musical Constraints with Markov Transition Probabilities to Improve the Generation of Creative Musical Structures
		Markov Chains and Music
		Musical Constraints
		Combining Musical Constraints and Transition Probabilities
			Tackling Drift and the End Point Problems with Stochastic Optimization
			Simulated Thermal Annealing
			Annealing Results
		Conclusions
		References
38. Dynamic Musical Orchestration Using Genetic Algorithms and a Spectro-Temporal Description of Musical Instruments
	Dynamic Musical Orchestration Using Genetic Algorithms and a Spectro-Temporal Description of Musical Instruments
		Introduction
		System Architecture
		Temporal Descriptor
			Existing Models
			Our Model
			Length Modification
				Modification by dilation.
				Modification by repetition.
			Results
		Experiments
		Conclusion and Future Work
39. Evolutionary Sound Synthesis: Rendering Spectrograms from Cellular Automata Histograms
	Evolutionary Sound Synthesis: Rendering Spectrograms from Cellular Automata Histograms
		Introduction
		The Multitype Voter Model
		Mapping Process: From Histograms to Spectrograms
		Features of the Multitype Voter Model Histogram Sequences
		Attacks and Releases
		Control
		Conclusion and Further Work
		References
40. Sound Agents
	Sound Agents
		Introduction
		Hardware Implementation of the Sound Agents System
		Swarm Intelligence
		A Declarative Language for Describing Agent Behaviors
			Goal Constraints and Local Search Constraint Solving
			Goal Constraints for Navigation
		Conclusion
		References
41. From Evolutionary Composition to Robotic Sonification
	From Evolutionary Composition to Robotic Sonification
		Introduction
		AURAL Architecture
			The OmniEye
			The Evolutionary Sound Interface
			Robotic Control
		Experiments
			Collective Behavior Affects Performance Control
		Conclusion
		References
42. Musical Composer Identification through Probabilistic and Feedforward Neural Networks
	Musical Composer Identification through Probabilistic and Feedforward Neural Networks
		Introduction
		Data Set and Data Extraction
		Classification Methods Tested
		Methodology and Experimental Results
		Discussion and Concluding Remarks
43. Using an Evolutionary Algorithm to Discover Low CO 2  Tours within a Travelling Salesman Problem
	Using an Evolutionary Algorithm to Discover Low CO2 Tours within a Travelling Salesman Problem
		Introduction and Motivation
		Previous Work
		Problem Description
			The Geographical Data Source
			Estimating Vehicle Emissions
			Emissions Calculations Using a Fuel Consumption Model
			Emissions Calculations Using a Simpler Model
		Experimental Method and Results
			Problem Instances
			The Evolutionary Algorithm Employed
			Experimental Method
			Results
		Conclusions and Future Work
44. A Genetic Algorithm for the Traveling Salesman Problem with Pickup and Delivery Using Depot Removal and Insertion Moves
	A Genetic Algorithm for the Traveling Salesman Problem
		Introduction
		An Evolutionary Approach for the TSPPD
			A Genetic Algorithm
			Tour Improvement Procedure
		Computational Experiments
		Conclusion
45. Fast Approximation Heuristics for Multi-Objective Vehicle Routing Problems
	Fast Approximation Heuristics for Multi-Objective Vehicle Routing Problems
		Introduction
		Problem Statement
		Solution Approach
			Encoding of Alternatives
			Constructive Phase: A Multi-objective Savings Heuristic
			Iterative Phase: Population-Based Multi-operator Search
		Experimental Investigation
			Benchmark Data
			Experiments and Results
		Conclusions
46. Particle Swarm Optimization and an Agent-Based Algorithm for a Problem of Staff Scheduling
	Particle Swarm Optimization and an Agent-Based Algorithm for a Problem of Staff Scheduling
		Introduction
		A Real-World Problem from Logistics
		Related Work
		PSO and Artificial Agent Approach
			PSO for This Application
			Artificial Agents for This Application
		Results and Discussion
		Conclusion and Future Work
47. A Math-Heuristic for the Multi-Level Capacitated Lot Sizing Problem with Carryover
	A Math-Heuristic for the Multi-Level Capacitated Lot Sizing Problem with Carryover
		Introduction
		A Formal Model for the MLCLSP-CO
		General Idea and Algorithm
		Incumbent Solution Generation: A Metaheuristic Scheme
		Computational Results
		Conclusions
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