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
Back matter
