This book constitutes the refereed proceedings of the International Workshops on the Applications of Evolutionary Computation, EvoApplications 2010, held in Istanbul, Turkey, in April 2010 colocated with the Evo* 2010 events. Thanks to the large number of submissions received, the proceedings for EvoApplications 2010 are divided across two volumes (LNCS 6024 and 6025). The present volume contains contributions for EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoMUSART, and EvoTRANSLOG. The 47 revised full papers presented were carefully reviewed and selected from a total of 86 submissions. 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 efficient EC methods for design and problem solving.
Author(s): Cecilia Di Chio, Anthony Brabazon, Marc Ebner, Muddassar Farooq, Andreas Fink, Jorn Grahl, Gary Greenfield, Penousal Machado, Michael O'Neill, Ernesto Tarantino, Neil Urquhart
Edition: 1st Edition.
Publisher: Springer
Year: 2010
Language: English
Pages: 503
Front matter......Page 1
Introduction......Page 29
Datasets......Page 30
Representation of Antigens and Antibodies......Page 31
Immune Algorithm......Page 32
Proposed Improvements on jREMISA......Page 33
Test Designs......Page 34
Results......Page 35
Conclusion......Page 37
References......Page 38
Introduction......Page 39
Principle AAA System Configuration......Page 41
Data Processing Unit......Page 42
The ANNP Unit......Page 44
Discussion of Simulation Results......Page 45
References......Page 47
Introduction......Page 49
AODV Parameter Tuning......Page 51
Optimization Strategy......Page 52
VANET Scenario and Mobility Models......Page 54
Simulation Results and Comparisons......Page 55
QoS Analysis......Page 56
Conclusions......Page 57
Introduction......Page 59
Problem Formulation......Page 60
Adaptive-Population-Size Genetic Algorithm......Page 61
Individual Representation......Page 62
Adaptive Population Size Adjustment......Page 63
Evolutionary Operations......Page 64
Network Layouts and Algorithm Configuration......Page 65
Results......Page 66
Concluding Remarks and Future Research......Page 67
Introduction......Page 69
Our Forced-Based GA......Page 70
Ergodic Homogeneous Finite Markov Chains......Page 71
Convergence of Ergodic Homogeneous Finite Markov Chain......Page 73
Simulation Experiments of Convergence for Our Forced-Based GA......Page 74
Conclusion and Future Work......Page 77
Introduction......Page 79
Particle Swarm Optimization......Page 81
Fitness Function......Page 82
Results and Discussion......Page 85
References......Page 87
Introduction......Page 89
Problem Definition......Page 90
Proposed ABC......Page 91
Results......Page 94
Conclusions......Page 97
References......Page 98
Introduction......Page 99
The TCP Protocol......Page 100
Packet Delay Modeling......Page 101
Delay Model Based TCP......Page 103
Network without Packet Loss......Page 105
Network with Packet Loss......Page 106
Conclusions......Page 107
Introduction......Page 109
Routing and Wavelength Assignment Problem......Page 111
Hyper-Heuristics......Page 112
Proposed Method......Page 113
Experimental Design......Page 114
Results......Page 115
Conclusion and Future Work......Page 117
Introduction......Page 119
Generalized Model of Connections......Page 120
Ad-hoc network graph - nodes level.......Page 121
Ad-hoc network graph - locations level.......Page 122
AntHocGeo Algorithm......Page 123
Connections Stability......Page 124
Overall Performance......Page 126
Conclusions......Page 127
Introduction......Page 129
Port Scans......Page 130
Evolutionary Model......Page 131
Fitness Evaluation......Page 132
Evolutionary Model......Page 134
Experiments and Results......Page 135
Analysis......Page 136
Conclusion and Future Work......Page 137
Introduction......Page 139
Access Network Model and Terminal Model......Page 140
Satisfaction Degree and Suitability Degree......Page 142
Gaming Analysis and Utility Calculation......Page 143
Mathematical Model......Page 144
Algorithm Procedure......Page 145
Conclusion......Page 147
References......Page 148
Introduction......Page 149
The Unit Commitment Problem......Page 150
Hyper-Heuristics......Page 151
Proposed Approach......Page 152
Experiments......Page 153
Experimental Results......Page 154
References......Page 157
Introduction......Page 159
Data and Methods......Page 161
The CART Model......Page 162
GP Evolved Pure Classification Rules (Class-GP)......Page 163
Discussion......Page 166
Conclusions......Page 167
Introduction......Page 169
CO2 Emission Modelling......Page 170
Experimental Approach......Page 171
Evidence......Page 174
Conclusions......Page 176
Introduction......Page 179
Multiobjective Evolutionary Algorithms......Page 180
Start-Up Optimisation of a Combined Cycle Power Plant......Page 181
Experimentations......Page 183
Results......Page 185
Discussion......Page 186
Conclusion and Future Work......Page 187
Introduction......Page 189
Problem Description......Page 190
Particle Swarm Optimization......Page 191
Negative Selection......Page 192
Experiments and Results......Page 193
Discussion......Page 195
Conclusion and Future Work......Page 197
Introduction......Page 199
Overview......Page 201
The Fitness Function......Page 202
Operators and Initialization......Page 203
GP Parameters, Data Periods and Consistency-of Performance Periods......Page 204
Results......Page 206
Concluding Summary and Discussion......Page 207
References......Page 208
Introduction......Page 210
Multi-stage Scenario Tree Generation......Page 211
Evolutionary Multi-stage Scenario Tree Generation......Page 212
Numerical Results......Page 215
Conclusion......Page 218
Introduction......Page 220
Background......Page 221
Evolving Dynamic Trade Execution Strategies......Page 222
Information Indicators......Page 223
Performance Evaluation......Page 224
Simulating an Artificial Market......Page 226
Results......Page 227
Conclusions and Future Work......Page 228
Introduction......Page 230
Background......Page 231
The Hybrid Forecasting System......Page 232
Calculating Profitability for each Genome.......Page 233
Additional Considerations......Page 234
Data preparation......Page 235
Comparison Approaches......Page 236
Results......Page 237
Conclusions......Page 238
Introduction......Page 240
Threshold Recurrent Reinforcement Learning......Page 242
Differential Sharpe Ratio for Online Learning......Page 243
Setup......Page 245
Results and Discussion......Page 246
Conclusion......Page 248
Introduction......Page 250
Index Tracking with Cardinality Constraints......Page 251
Nature-Inspired Optimisation Algorithms......Page 252
Traditional vs. Fuzzy Enhanced Indexation......Page 253
Sample Data and Experimental Design......Page 254
Discussion - Further Research......Page 257
Introduction......Page 260
First Passage Time in Credit Risk Models......Page 261
Multivariate Jump-Diffusion Processes and Monte Carlo Simulations......Page 263
Density Functions, Default Rates, and Correlated Default......Page 266
Conclusion......Page 268
Introduction......Page 270
Black–Scholes–Merton......Page 271
The Heston Model......Page 272
Calibrating the Model Parameters......Page 273
Calibrating the Heston Model......Page 275
Conclusion......Page 278
Introduction......Page 279
Rule-Based Policies......Page 280
Grammatical Representation......Page 282
Evolution of Trading Policies......Page 283
Methodology......Page 284
Results......Page 285
Example Evolved Policy......Page 286
Conclusion and Future Work......Page 287
Introduction......Page 289
Background and Motivation......Page 290
The Top-Level Behavior......Page 291
The Generator Component......Page 293
The Analyzer Component......Page 294
I3 Experience......Page 295
Summary and Future Work......Page 297
Introduction......Page 299
Evolutionary Context Free Art......Page 300
Crossover Operator......Page 301
Mutation Operators......Page 302
Fitness Functions......Page 304
Experimental Results......Page 305
Conclusions and Future Work......Page 307
Introduction......Page 309
Related Work......Page 310
Colour Adjustment......Page 311
Tile Size Variation......Page 313
Colour Adjustment......Page 314
Tile Size Variation......Page 315
Conclusions......Page 317
Introduction......Page 319
Our Cellular Morphogenesis Evolutionary Art System......Page 320
Evolutionary Exploration Using Fitness Functions......Page 322
Analysis of the Source Material......Page 323
Evolutionary Refinement of the Source Material......Page 324
Conclusion......Page 327
Introduction......Page 329
Image Complexity Estimation......Page 330
Image Order Estimation......Page 331
Genetic Programming.......Page 332
Evolutionary and Learning Process.......Page 333
Accuracy of Prediction.......Page 334
Generation Results.......Page 335
Conclusions and Future Work......Page 337
Research Question......Page 339
Four Aesthetic Measures......Page 340
Arabitat: The Art Habitat......Page 341
Results......Page 343
Cross Evaluation......Page 346
Future Work......Page 347
The Problem of Fitness Functions for Evolutionary Art......Page 349
Computational Aesthetic Evaluation......Page 350
The Future of Aesthetic Evaluation for Evolutionary Art......Page 351
Complexification in Nature and Genetic Representation......Page 352
The Problem of Art Theory for Evolutionary Art......Page 354
Evolutionary Art Theory and Truth to Process......Page 355
References......Page 356
Introduction......Page 359
Background......Page 360
Audio Processing......Page 361
ANN Training......Page 363
Dancing to Raw Audio......Page 364
Discussion......Page 367
Conclusion......Page 368
Introduction......Page 369
Previous Work......Page 370
Generative......Page 371
Interactive......Page 373
Virtual......Page 374
Evolutionary......Page 375
Discussion......Page 376
Conclusions and Future Work......Page 377
Introduction......Page 379
The Neural Networks......Page 381
Training, Validation and Test Results......Page 385
Conclusions......Page 387
Markov Chains and Music......Page 389
Musical Constraints......Page 391
Combining Musical Constraints and Transition Probabilities......Page 392
Tackling Drift and the End Point Problems with Stochastic Optimization......Page 393
Simulated Thermal Annealing......Page 394
Annealing Results......Page 396
References......Page 397
Introduction......Page 399
System Architecture......Page 400
Existing Models......Page 401
Our Model......Page 402
Modification by dilation.......Page 404
Results......Page 405
Conclusion and Future Work......Page 407
Introduction......Page 409
The Multitype Voter Model......Page 410
Mapping Process: From Histograms to Spectrograms......Page 411
Features of the Multitype Voter Model Histogram Sequences......Page 412
Attacks and Releases......Page 414
Control......Page 416
References......Page 418
Introduction......Page 419
Hardware Implementation of the Sound Agents System......Page 420
Swarm Intelligence......Page 421
Goal Constraints and Local Search Constraint Solving......Page 423
Goal Constraints for Navigation......Page 425
References......Page 426
Introduction......Page 429
AURAL Architecture......Page 430
The Evolutionary Sound Interface......Page 431
Experiments......Page 434
Collective Behavior Affects Performance Control......Page 436
References......Page 437
Introduction......Page 439
Data Set and Data Extraction......Page 440
Classification Methods Tested......Page 441
Methodology and Experimental Results......Page 443
Discussion and Concluding Remarks......Page 447
Introduction and Motivation......Page 449
The Geographical Data Source......Page 450
Emissions Calculations Using a Fuel Consumption Model......Page 451
Emissions Calculations Using a Simpler Model......Page 452
The Evolutionary Algorithm Employed......Page 453
Results......Page 454
Conclusions and Future Work......Page 456
Introduction......Page 459
A Genetic Algorithm......Page 461
Tour Improvement Procedure......Page 462
Computational Experiments......Page 464
Conclusion......Page 467
Introduction......Page 469
Problem Statement......Page 470
Encoding of Alternatives......Page 471
Iterative Phase: Population-Based Multi-operator Search......Page 472
Experiments and Results......Page 474
Conclusions......Page 477
Introduction......Page 479
A Real-World Problem from Logistics......Page 480
Related Work......Page 481
PSO for This Application......Page 482
Artificial Agents for This Application......Page 483
Results and Discussion......Page 486
Conclusion and Future Work......Page 488
Introduction......Page 490
A Formal Model for the MLCLSP-CO......Page 491
General Idea and Algorithm......Page 492
Incumbent Solution Generation: A Metaheuristic Scheme......Page 495
Computational Results......Page 497
Conclusions......Page 498
Back matter......Page 500
