GECCO 2005: Washington, DC, USA

Artificial life, evolutionary robotics, and adaptive behavior

• Chandana Paul, Hod Lipson, Francisco J. Valero Cuevas:
  Evolutionary form-finding of tensegrity structures. 3-10
  
• Vinod K. Valsalam, James A. Bednar, Risto Miikkulainen:
  Constructing good learners using evolved pattern generators. 11-18
  
• Justin Schonfeld, Daniel A. Ashlock:
  A study of evolutionary robustness in stochastically tiled polyominos. 19-26
  
• Ricardo Landa Becerra, Carlos A. Coello Coello:
  Optimization with constraints using a cultured differential evolution approach. 27-34
  
• Matthias Scheutz, Paul W. Schermerhorn:
  Predicting population dynamics and evolutionary trajectories based on performance evaluations in alife simulations. 35-42
  
• Keith L. Downing:
  The predictive basis of situated and embodied artificial intelligence. 43-50
  
• Michelle McPartland, Stefano Nolfi, Hussein A. Abbass:
  Emergence of communication in competitive multi-agent systems: a pareto multi-objective approach. 51-58
  
• Daniel A. Ashlock, Eun-Youn Kim:
  The impact of cellular representation on finite state agents for prisoner's dilemma. 59-66
  
• Hong-Long Liang, Chungnan Lee, Jain-Shing Wu:
  Multiplex PCR primer design for gene family using genetic algorithm. 67-74
  
• A. E. Eiben, Martijn C. Schut, T. Toma:
  Comparing multicast and newscast communication in evolving agent societies. 75-81
  
• Timothy G. W. Gordon, Peter J. Bentley:
  Bias and scalability in evolutionary development. 83-90
  
• Sean Luke:
  Evolutionary computation and the c-value paradox. 91-97
  
• John Rieffel, Jordan B. Pollack:
  Automated assembly as situated development: using artificial ontogenies to evolve buildable 3-D objects. 99-106
  
• Ron Breukelaar, Thomas Bäck:
  Using a genetic algorithm to evolve behavior in multi dimensional cellular automata: emergence of behavior. 107-114
  
• Ehud Schlessinger, Peter J. Bentley, R. Beau Lotto:
  Evolving visually guided agents in an ambiguous virtual world. 115-120
  
• Renato Reder Cazangi, Fernando J. Von Zuben, Maurício F. Figueiredo:
  Autonomous navigation system applied to collective robotics with ant-inspired communication. 121-128
  
• Anthony Brabazon, Arlindo Silva, Tiago Ferra de Sousa, Michael O'Neill, Robin Matthews, Ernesto Costa:
  Agent-based modelling of product invention. 129-136
  
• Andrew Stout, Lee Spector:
  Validation of evolutionary activity metrics for long-term evolutionary dynamics. 137-142
  

Poster Session: Artificial life, evolutionary robotics, and adaptive behavior

• Tadahiko Murata, Masatoshi Yamaguchi:
  Neighboring crossover to improve GA-based Q-learning method for multi-legged robot control. 145-146
  
• Gary B. Parker, Ramona Georgescu:
  Evolution of multi-loop controllers for fixed morphology with a cyclic genetic algorithm. 147-148
  
• Artur Matos, Reiji Suzuki, Takaya Arita:
  Evolutionary models for maternal effects in simulated developmental systems. 149-150
  

Ant colony optimization and swarm intelligence

• Horst Wedde, Muddassar Farooq, Thorsten Pannenbaecker, Bjoern Vogel, Christian Mueller, Johannes Meth, René Jeruschkat:
  BeeAdHoc: an energy efficient routing algorithm for mobile ad hoc networks inspired by bee behavior. 153-160
  
• Matthew Settles, Terence Soule:
  Breeding swarms: a GA/PSO hybrid. 161-168
  
• Riccardo Poli, Cecilia Di Chio, William B. Langdon:
  Exploring extended particle swarms: a genetic programming approach. 169-176
  
• Swagatam Das, Amit Konar, Uday Kumar Chakraborty:
  Improving particle swarm optimization with differentially perturbed velocity. 177-184
  
• Matthew Settles, Paul Nathan, Terence Soule:
  Breeding swarms: a new approach to recurrent neural network training. 185-192
  
• Christopher K. Monson, Kevin D. Seppi:
  Bayesian optimization models for particle swarms. 193-200
  
• James Kennedy:
  Dynamic-probabilistic particle swarms. 201-207
  
• Angel Eduardo Muñoz Zavala, Arturo Hernández Aguirre, Enrique Raúl Villa Diharce:
  Constrained optimization via particle evolutionary swarm optimization algorithm (PESO). 209-216
  
• Vegard Hartmann:
  Evolving agent swarms for clustering and sorting. 217-224
  
• Efrén Mezura-Montes, Jesús Velázquez-Reyes, Carlos A. Coello Coello:
  Promising infeasibility and multiple offspring incorporated to differential evolution for constrained optimization. 225-232
  
• Mark Fleischer:
  Scale invariant pareto optimality: a meta--formalism for characterizing and modeling cooperativity in evolutionary systems. 233-240
  
• Christopher K. Monson, Kevin D. Seppi:
  Exposing origin-seeking bias in PSO. 241-248
  
• Wai-Kuan Foong, Holger R. Maier, Angus R. Simpson:
  Ant colony optimization for power plant maintenance scheduling optimization. 249-256
  
• Carlo R. Raquel, Prospero C. Naval Jr.:
  An effective use of crowding distance in multiobjective particle swarm optimization. 257-264
  

Poster Session: Ant colony optimization and swarm intelligence

• Bo-Fu Liu, Hung-Ming Chen, Jian-Hung Chen, Shiow-Fen Hwang, Shinn-Ying Ho:
  MeSwarm: memetic particle swarm optimization. 267-268
  
• Mohammed El-Abd, Mohamed Kamel:
  Factors governing the behavior of multiple cooperating swarms. 269-270
  
• Thang Nguyen Bui, Mufit Colpan:
  Solving geometric TSP with ants. 271-272
  
• Thomas Schmickl, Ronald Thenius, Karl Crailsheim:
  Simulating swarm intelligence in honey bees: foraging in differently fluctuating environments. 273-274
  
• Rafael Bello, Ann Nowé, Yaile Caballero, Yudel Gómez, Peter Vrancx:
  A model based on ant colony system and rough set theory to feature selection. 275-276
  
• Zhihua Cui, Jianchao Zeng:
  A modified particle swarm optimization predicted by velocity. 277-278
  

Artificial immune systems

• Zhou Ji, Dipankar Dasgupta:
  Estimating the detector coverage in a negative selection algorithm. 281-288
  
• Fabrício Olivetti de França, Fernando J. Von Zuben, Leandro Nunes de Castro:
  An artificial immune network for multimodal function optimization on dynamic environments. 289-296
  
• Fabio A. González, Juan Carlos Galeano, Diego Alexander Rojas, Angélica Veloza-Suan:
  Discriminating and visualizing anomalies using negative selection and self-organizing maps. 297-304
  
• Zaiyi Guo, Hann Kwang Han, Joc Cing Tay:
  Sufficiency verification of HIV-1 pathogenesis based on multi-agent simulation. 305-312
  
• Peter Spellward, Tim Kovacs:
  On the contribution of gene libraries to artificial immune systems. 313-319
  
• Thomas Stibor, Philipp H. Mohr, Jonathan Timmis, Claudia Eckert:
  Is negative selection appropriate for anomaly detection? 321-328
  
• Jui-Yu Wu, Yun-Kung Chung:
  Artificial immune system for solving generalized geometric problems: a preliminary results. 329-336
  
• Joseph M. Shapiro, Gary B. Lamont, Gilbert L. Peterson:
  An evolutionary algorithm to generate hyper-ellipsoid detectors for negative selection. 337-344
  
• Xiaoshu Hang, Honghua Dai:
  Applying both positive and negative selection to supervised learning for anomaly detection. 345-352
  
• Ian Nunn, Tony White:
  The application of antigenic search techniques to time series forecasting. 353-360
  
• Juan Carlos Galeano, Angélica Veloza-Suan, Fabio A. González:
  A comparative analysis of artificial immune network models. 361-368
  

Poster Session: Artificial immune systems

• Helder Knidel, Leandro Nunes de Castro, Fernando J. Von Zuben:
  RABNET: a real-valued antibody network for data clustering. 371-372
  
• Maoguo Gong, Licheng Jiao, Haifeng Du, Ronghua Shang, Bin Lu:
  Performance assessment of an artificial immune system multiobjective optimizer by two improved metrics. 373-374
  

Biological applications

• Joshua L. Payne, Margaret J. Eppstein:
  A hybrid genetic algorithm with pattern search for finding heavy atoms in protein crystals. 377-384
  
• Thang Nguyen Bui, Gnanasekaran Sundarraj:
  An efficient genetic algorithm for predicting protein tertiary structures in the 2D HP model. 385-392
  
• Praveen Koduru, Sanjoy Das, Stephen Welch, Judith L. Roe, Zenaida P. Lopez-Dee:
  A co-evolutionary hybrid algorithm for multi-objective optimization of gene regulatory network models. 393-399
  
• Rolv Seehuus, Amund Tveit, Ole Edsberg:
  Discovering biological motifs with genetic programming. 401-408
  
• Gloria Childress Townsend, Wade N. Hazel, Rick Smock:
  Using evolutionary computation methods to support analytical models for the evolution and maintenance of conditional strategies in chthamalus anisopoma. 409-414
  
• Leon Poladian:
  A GA for maximum likelihood phylogenetic inference using neighbour-joining as a genotype to phenotype mapping. 415-422
  
• Tim Hohm, Daniel Hoffmann:
  A multi-objective evolutionary approach to peptide structure redesign and stabilization. 423-429
  
• Habtom W. Ressom, Rency S. Varghese, Daniel Saha, Eduard Orvisky, Lenka Goldman, Emanuel F. Petricoin, Thomas P. Conrads, Timothy D. Veenstra, Mohamed Abdel-Hamid, Christopher A. Loffredo, Radoslav Goldman:
  Particle swarm optimization for analysis of mass spectral serum profiles. 431-438
  
• Nasimul Noman, Hitoshi Iba:
  Inference of gene regulatory networks using s-system and differential evolution. 439-446
  
• Dongsheng Che, Yinglei Song, Khaled Rasheed:
  MDGA: motif discovery using a genetic algorithm. 447-452
  
• Topon Kumar Paul, Hitoshi Iba:
  Extraction of informative genes from microarray data. 453-460
  
• Hiram A. Firpi, Erik D. Goodman, Javier R. Echauz:
  Epileptic seizure detection by means of genetically programmed artificial features. 461-466
  

Poster Session: Biological applications

• Christian Spieth, Felix Streichert, Nora Speer, Andreas Zell:
  Identifying valid solutions for the inference of regulatory networks. 469-470
  
• David E. Cairns, G. J. Cameron, T. J. Wess:
  Evolving an improved axial structure for fibrillar collagen. 471-472
  
• Jesús S. Aguilar-Ruiz, Federico Divina:
  GA-based approach to discover meaningful biclusters. 473-474
  
• Feng-Mao Lin, Hsien-Da Huang, Hsi-Yuan Huang, Jorng-Tzong Horng:
  Primer design for multiplex PCR using a genetic algorithm. 475-476
  
• Pasut Seeluangsawat, Prabhas Chongstitvatana:
  A multiple objective evolutionary algorithm for multiple sequence alignment. 477-478
  
• Kay C. Wiese, Andrew Hendriks, Alain Deschênes, Belgacem Ben Youssef:
  The impact of pseudorandom number quality on P-RnaPredict, a parallel genetic algorithm for RNA secondary structure prediction. 479-480
  

Coevolution

• Edwin D. de Jong:
  The MaxSolve algorithm for coevolution. 483-489
  
• Faustino J. Gomez, Jürgen Schmidhuber:
  Co-evolving recurrent neurons learn deep memory POMDPs. 491-498
  
• Sevan G. Ficici:
  Monotonic solution concepts in coevolution. 499-506
  
• Elena Popovici, Kenneth A. De Jong:
  Understanding cooperative co-evolutionary dynamics via simple fitness landscapes. 507-514
  
• Pablo Funes, Enrique Pujals:
  Intransitivity revisited coevolutionary dynamics of numbers games. 515-521
  
• Nathan Williams, Melanie Mitchell:
  Investigating the success of spatial coevolution. 523-530
  
• Josh C. Bongard, Hod Lipson:
  'Managed challenge' alleviates disengagement in co-evolutionary system identification. 531-538
  
• Anthony Bucci, Jordan B. Pollack:
  On identifying global optima in cooperative coevolution. 539-544
  
• Chien-Feng Huang, Luis Mateus Rocha:
  Tracking extrema in dynamic environments using a coevolutionary agent-based model of genotype edition. 545-552
  

Poster Session: Coevolution

• Deborah Vakas Duong, John J. Grefenstette:
  The emulation of social institutions as a method of coevolution. 555-556
  
• Jeffrey Horn:
  Shape nesting by coevolving species. 557-558
  
• Christophe Philemotte, Hugues Bersini:
  Intrinsic emergence boosts adaptive capacity. 559-560
  

Evolutionary combinatorial optimization

• Katharina Anna Lehmann, Michael Kaufmann:
  Evolutionary algorithms for the self-organized evolution of networks. 563-570
  
• Christian Gunia:
  On the analysis of the approximation capability of simple evolutionary algorithms for scheduling problems. 571-578
  
• Benjamin Skellett, Benjamin Cairns, Nicholas Geard, Bradley Tonkes, Janet Wiles:
  Maximally rugged NK landscapes contain the highest peaks. 579-584
  
• Bryant A. Julstrom:
  The blob code is competitive with edge-sets in genetic algorithms for the minimum routing cost spanning tree problem. 585-590
  
• Kagan Tumer, Adrian K. Agogino:
  Coordinating multi-rover systems: evaluation functions for dynamic and noisy environments. 591-598
  
• Anne Defaweux, Tom Lenaerts, Jano I. van Hemert, Johan Parent:
  Transition models as an incremental approach for problem solving in evolutionary algorithms. 599-606
  
• Bryant A. Julstrom:
  Greedy, genetic, and greedy genetic algorithms for the quadratic knapsack problem. 607-614
  
• German Hernandez, Kenneth Wilder, Fernando Niño, Julian Garcia:
  Towards a self-stopping evolutionary algorithm using coupling from the past. 615-620
  
• Jing Tang, Meng-Hiot Lim, Yew-Soon Ong, Meng Joo Er:
  Solving large scale combinatorial optimization using PMA-SLS. 621-628
  
• Yourim Yoon, Yong-Hyuk Kim, Byung Ro Moon:
  An evolutionary lagrangian method for the 0/1 multiple knapsack problem. 629-635
  
• Hugo Terashima-Marín, E. J. Flores-Álvarez, Peter Ross:
  Hyper-heuristics and classifier systems for solving 2D-regular cutting stock problems. 637-643
  

Poster Session: Evolutionary combinatorial optimization

• Lina Perelman, Avi Ostfeld:
  Water distribution systems optimal design using cross entropy. 647-648
  
• István Borgulya:
  A hybrid evolutionary algorithm for the p-median problem. 649-650
  
• Zong Woo Geem, Kang Seok Lee, Chung-Li Tseng:
  Harmony search for structural design. 651-652
  

Estimation of distribution algorithms

• Martin V. Butz, Martin Pelikan, Xavier Llorà, David E. Goldberg:
  Extracted global structure makes local building block processing effective in XCS. 655-662
  
• Martin Pelikan, Kumara Sastry, David E. Goldberg:
  Multiobjective hBOA, clustering, and scalability. 663-670
  
• Kumara Sastry, Hussein A. Abbass, David E. Goldberg, D. D. Johnson:
  Sub-structural niching in estimation of distribution algorithms. 671-678
  
• Stefan Droste:
  Not all linear functions are equally difficult for the compact genetic algorithm. 679-686
  
• Ivan Tanev:
  Learned mutation strategies in genetic programming for evolution and adaptation of simulated snakebot. 687-694
  
• Alden H. Wright, Sandeep Pulavarty:
  On the convergence of an estimation of distribution algorithm based on linkage discovery and factorization. 695-702
  
• Jun Sakuma, Shigenobu Kobayashi:
  Real-coded crossover as a role of kernel density estimation. 703-710
  
• Shengxiang Yang:
  Population-based incremental learning with memory scheme for changing environments. 711-718
  
• Bo Yuan, Marcus Gallagher:
  On the importance of diversity maintenance in estimation of distribution algorithms. 719-726
  
• Siddhartha Shakya, John A. W. McCall, Deryck F. Brown:
  Using a Markov network model in a univariate EDA: an empirical cost-benefit analysis. 727-734
  
• Cláudio F. Lima, Kumara Sastry, David E. Goldberg, Fernando G. Lobo:
  Combining competent crossover and mutation operators: a probabilistic model building approach. 735-742
  

Poster Session: Estimation of distribution algorithms

• Yi Hong, Qingsheng Ren, Jin Zeng:
  Genetic drift in univariate marginal distribution algorithm. 745-746
  
• Moshe Looks, Ben Goertzel, Cassio Pennachin:
  Learning computer programs with the bayesian optimization algorithm. 747-748
  
• Sergio Ivvan Valdez Peña, Salvador Botello Rionda, Arturo Hernández Aguirre:
  Multiobjective shape optimization with constraints based on estimation distribution algorithms and correlated information. 749-750
  
• Chien-Feng Huang, Stefan Bieniawski, David H. Wolpert, Charlie E. M. Strauss:
  A comparative study of probability collectives based multi-agent systems and genetic algorithms. 751-752
  

Evolutionary multiobjective optimization

• Peter A. N. Bosman, Edwin D. de Jong:
  Exploiting gradient information in numerical multi--objective evolutionary optimization. 755-762
  
• Frank Neumann, Ingo Wegener:
  Minimum spanning trees made easier via multi-objective optimization. 763-769
  
• Mian Li, Shapour Azarm, Vikrant Aute:
  A multi-objective genetic algorithm for robust design optimization. 771-778
  
• Lam Thu Bui, Hussein A. Abbass, Daryl Essam:
  Fitness inheritance for noisy evolutionary multi-objective optimization. 779-785
  
• Hisao Ishibuchi, Kaname Narukawa:
  Comparison of evolutionary multiobjective optimization with rference solution-based single-objective approach. 787-794
  
• Yang Zhang, Peter Rockett:
  Evolving optimal feature extraction using multi-objective genetic programming: a methodology and preliminary study on edge detection. 795-802
  
• Mary E. Kurz, Sarah Canterbury:
  Minimizing total flowtime and maximum earliness on a single machine using multiple measures of fitness. 803-809
  
• Kai Xu, Sushil J. Louis, Roberto C. Mancini:
  A scalable parallel genetic algorithm for x-ray spectroscopic analysis. 811-816
  
• Hisao Ishibuchi, Kaname Narukawa, Yusuke Nojima:
  An empirical study on the handling of overlapping solutions in evolutionary multiobjective optimization. 817-824
  

Poster Session: Evolutionary multiobjective optimization

• Karlheinz Schmitt, Jörn Mehnen, Thomas Michelitsch:
  Using predators and preys in evolution strategies. 827-828
  
• Shinya Watanabe, Kazutoshi Sakakibara:
  The effectiveness of multiobjective optimizer in single-objective optimization enviroment. 829-830
  

Evolutionary strategies and evolutionary programming

• Tobias Storch:
  On the impact of objective function transformations on evolutionary and black-box algorithms. 833-840
  
• Thomas Jansen, Ulf Schellbach:
  Theoretical analysis of a mutation-based evolutionary algorithm for a tracking problem in the lattice. 841-848
  
• Jens Jägersküpper, Carsten Witt:
  Rigorous runtime analysis of a (µ+1)ES for the sphere function. 849-856
  
• Anne Auger, Marc Schoenauer, Olivier Teytaud:
  Local and global order 3/2 convergence of a surrogate evolutionary algorithm. 857-864
  
• Mike Preuss, Lutz Schönemann, Michael Emmerich:
  Counteracting genetic drift and disruptive recombination in (µ_, ⁺lambda)-EA on multimodal fitness landscapes. 865-872
  
• Xiaodong Li:
  Efficient differential evolution using speciation for multimodal function optimization. 873-880
  
• Junhong Liu, Jouni Lampinen:
  A differential evolution based incremental training method for RBF networks. 881-888
  
• Pei Yee Ho, Kazuyuki Shimizu:
  Simple addition of ranking method for constrained optimization in evolutionary algorithms. 889-896
  
• Michael Nashvili, Markus Olhofer, Bernhard Sendhoff:
  Morphing methods in evolutionary design optimization. 897-904
  
• Tanasanee Phienthrakul, Boonserm Kijsirikul:
  Evolutionary strategies for multi-scale radial basis function kernels in support vector machines. 905-911
  

Poster Session: Evolutionary strategies and evolutionary programming

• Ofer M. Shir, Thomas Bäck:
  Niching in evolution strategies. 915-916
  
• Oliver Kramer, Chuan-Kang Ting, Hans Kleine Büning:
  A mutation operator for evolution strategies to handle constrained problems. 917-918
  
• Karlheinz Schmitt:
  Using gene deletion and gene duplication in evolution strategies. 919-920
  
• Sadiq M. Sait, Syed Sanaullah, Ali Mustafa Zaidi, Mustafa I. Ali:
  Comparative evaluation of parallelization strategies for evolutionary and stochastic heuristics. 921-922
  
• Lutz Schönemann:
  Optimal number of evolution strategies mutation step sizes in dynamic environments. 923-924
  

Evolutionary hardware

• Didier Keymeulen, Wolfgang Fink, Michael I. Ferguson, Chris Peay, Boris Oks, Richard Terrile, Karl Yee:
  Evolutionary computation applied to the tuning of MEMS gyroscopes. 927-932
  
• Saranyan Vigraham, John C. Gallagher, Sanjay K. Boddhu:
  Evolving analog controllers for correcting thermoacoustic instability in real hardware. 933-940
  
• Lucian Prodan, Mihai Udrescu, Mircea Vladutiu:
  Multiple-level concatenated coding in embryonics: a dependability analysis. 941-948
  
• Malay Kumar Pakhira, Rajat K. De:
  A hardware pipeline for function optimization using genetic algorithms. 949-956
  
• Rusty Hunt, Gregory Hornby, Jason D. Lohn:
  Toward evolved flight. 957-964
  

Meta-heuristics and local search

• Nasimul Noman, Hitoshi Iba:
  Enhancing differential evolution performance with local search for high dimensional function optimization. 967-974
  
• John F. McLoughlin III, Walter Cedeño:
  The enhanced evolutionary tabu search and its application to the quadratic assignment problem. 975-982
  
• David Quintana, Cristóbal Luque del Arco-Calderón, Pedro Isasi:
  Evolutionary rule-based system for IPO underpricing prediction. 983-989
  
• Swagatam Das, Amit Konar, Uday Kumar Chakraborty:
  Two improved differential evolution schemes for faster global search. 991-998
  
• Abraham Duarte, Ángel Sánchez, Felipe Fernández, Raúl Cabido:
  A low-level hybridization between memetic algorithm and VNS for the max-cut problem. 999-1006
  

Poster Session: Meta-heuristics and local search

• Salem F. Adra, Ian Griffin, Peter J. Fleming:
  Hybrid multiobjective genetic algorithm with a new adaptive local search process. 1009-1010
  

Search-based software engineering

• Phil McMinn, Mike Holcombe:
  Evolutionary testing of state-based programs. 1013-1020
  
• Lionel C. Briand, Yvan Labiche, Marwa Shousha:
  Stress testing real-time systems with genetic algorithms. 1021-1028
  
• Mark Harman, Stephen Swift, Kiarash Mahdavi:
  An empirical study of the robustness of two module clustering fitness functions. 1029-1036
  
• Concettina Del Grosso, Giuliano Antoniol, Massimiliano Di Penta, Philippe Galinier, Ettore Merlo:
  Improving network applications security: a new heuristic to generate stress testing data. 1037-1043
  
• Olaf Seng, Markus Bauer, Matthias Biehl, Gert Pache:
  Search-based improvement of subsystem decompositions. 1045-1051
  
• Stefan Wappler, Frank Lammermann:
  Using evolutionary algorithms for the unit testing of object-oriented software. 1053-1060
  
• Yuan Zhan, John A. Clark:
  Search-based mutation testing for Simulink models. 1061-1068
  
• Gerardo Canfora, Massimiliano Di Penta, Raffaele Esposito, Maria Luisa Villani:
  An approach for QoS-aware service composition based on genetic algorithms. 1069-1075
  

Poster Session: Search-based software engineering

• Andrew Sutton, Huzefa H. Kagdi, Jonathan I. Maletic, L. Gwenn Volkert:
  Hybridizing evolutionary algorithms and clustering algorithms to find source-code clones. 1079-1080
  
• Karnig Derderian, Robert M. Hierons, Mark Harman, Qiang Guo:
  Generating feasible input sequences for extended finite state machines (EFSMs) using genetic algorithms. 1081-1082
  
• Frank Lammermann, Stefan Wappler:
  Benefits of software measures for evolutionary white-box testing. 1083-1084
  
• Joseph Haas, Maxim Peysakhov, Spiros Mancoridis:
  GA-based parameter tuning for multi-agent systems. 1085-1086
  

Genetic algorithms

• Shengxiang Yang:
  Memory-based immigrants for genetic algorithms in dynamic environments. 1115-1122
  
• Enrique Alba, Hugo Alfonso, Bernabé Dorronsoro:
  Advanced models of cellular genetic algorithms evaluated on SAT. 1123-1130
  
• Artem Sokolov, Darrell Whitley:
  Unbiased tournament selection. 1131-1138
  
• Raúl Giráldez, Jesús S. Aguilar-Ruiz:
  Feature influence for evolutionary learning. 1139-1145
  
• U. Chandimal de Silva, Joe Suzuki:
  On the stationary distribution of GAs with fixed crossover probability. 1147-1151
  
• Nicholas Freitag McPhee, Ellery Fussell Crane:
  A theoretical analysis of the HIFF problem. 1153-1160
  
• Dirk Sudholt:
  Crossover is provably essential for the ising model on trees. 1161-1167
  
• Dong-il Seo, Byung Ro Moon:
  Computing the epistasis variance of large-scale traveling salesman problems. 1169-1176
  
• Ivan I. Garibay, Annie S. Wu, Ozlem O. Garibay:
  On favoring positive correlations between form and quality of candidate solutions via the emergence of genomic self-similarity. 1177-1184
  
• Chongshan Zhang, Khaled Rasheed:
  Improving GA search reliability using maximal hyper-rectangle analysis. 1185-1192
  
• Helio J. C. Barbosa, Afonso C. C. Lemonge:
  A genetic algorithm encoding for a class of cardinality constraints. 1193-1200
  
• Edwin D. de Jong, Richard A. Watson, Dirk Thierens:
  On the complexity of hierarchical problem solving. 1201-1208
  
• Monte Lunacek, L. Darrell Whitley, James N. Knight:
  Measuring mobility and the performance of global search algorithms. 1209-1216
  
• Tian-Li Yu, Kumara Sastry, David E. Goldberg:
  Linkage learning, overlapping building blocks, and systematic strategy for scalable recombination. 1217-1224
  
• Shimon Whiteson, Peter Stone, Kenneth O. Stanley, Risto Miikkulainen, Nate Kohl:
  Automatic feature selection in neuroevolution. 1225-1232
  
• J. Neal Richter, John Paxton, Alden H. Wright:
  EA models and population fixed-points versus mutation rates for functions of unitation. 1233-1240
  
• Sung-Soon Choi, Kyomin Jung, Jeong Han Kim:
  Phase transition in a random NK landscape model. 1241-1248
  
• Hal Stringer, Annie S. Wu:
  Behavior of finite population variable length genetic algorithms under random selection. 1249-1255
  
• Sima Uyar, Gülsen Eryigit:
  Improvements to penalty-based evolutionary algorithms for the multi-dimensional knapsack problem using a gene-based adaptive mutation approach. 1257-1264
  
• Lee K. Graham, Hassan Masum, Franz Oppacher:
  Statistical analysis of heuristics for evolving sorting networks. 1265-1270
  
• Shane Legg, Marcus Hutter:
  Fitness uniform deletion: a simple way to preserve diversity. 1271-1278
  
• Abdullah Konak, Alice E. Smith:
  Designing resilient networks using a hybrid genetic algorithm approach. 1279-1285
  
• Yossi Borenstein, Riccardo Poli:
  Information landscapes and the analysis of search algorithms. 1287-1294
  
• Zbigniew Skolicki, Kenneth A. De Jong:
  The influence of migration sizes and intervals on island models. 1295-1302
  
• Maria Teresa Iglesias, Bart Naudts, Alain Verschoren, Concepcion Vidal:
  Walsh transforms, balanced sum theorems and partition coefficients over multary alphabets. 1303-1308
  
• Adrian K. Agogino, Kagan Tumer, Risto Miikkulainen:
  Efficient credit assignment through evaluation function decomposition. 1309-1316
  
• Ayse S. Yilmaz, Annie S. Wu:
  Preservation of genetic redundancy in the existence of developmental error and fitness assignment error. 1317-1324
  
• Kai Wing Tang, Ray A. Jarvis:
  From supervised ranking to evolving behaviours of a robotic team. 1325-1332
  
• Mario Giacobini, Marco Tomassini, Andrea Tettamanzi:
  Takeover time curves in random and small-world structured populations. 1333-1340
  
• Shuhei Kimura, Koki Matsumura:
  Genetic algorithms using low-discrepancy sequences. 1341-1346
  
• Jun Sakuma, Shigenobu Kobayashi:
  Latent variable crossover for k-tablet structures and its application to lens design problems. 1347-1354
  
• Alexei V. Samsonovich, Kenneth A. De Jong:
  Pricing the 'free lunch' of meta-evolution. 1355-1362
  
• Xavier Llorà, Kumara Sastry, David E. Goldberg, Abhimanyu Gupta, Lalitha Lakshmi:
  Combating user fatigue in iGAs: partial ordering, support vector machines, and synthetic fitness. 1363-1370
  
• Jeffrey K. Bassett, Mitchell A. Potter, Kenneth A. De Jong:
  Applying price's equation to survival selection. 1371-1378
  
• David Pardoe, Michael S. Ryoo, Risto Miikkulainen:
  Evolving neural network ensembles for control problems. 1379-1384
  
• Carlos Kavka, Patricia Roggero, Marc Schoenauer:
  Evolution of Voronoi based fuzzy recurrent controllers. 1385-1392
  
• Yong-Hyuk Kim, Byung Ro Moon:
  New topologies for genetic search space. 1393-1399
  
• William A. Greene:
  Schema disruption in tree-structured chromosomes. 1401-1408
  
• Lixin X. Ding, Jinghu Yu:
  Some theoretical results about the computation time of evolutionary algorithms. 1409-1415
  
• Shin Ando, Jun Sakuma, Shigenobu Kobayashi:
  Adaptive isolation model using data clustering for multimodal function optimization. 1417-1424
  
• Yossi Borenstein, Riccardo Poli:
  Information landscapes and problem hardness. 1425-1431
  
• Jürgen Branke, Erdem Salihoglu, Sima Uyar:
  Towards an analysis of dynamic environments. 1433-1440
  
• Guofang Nan, Minqiang Li, Jisong Kou:
  Multi-level genetic algorithm (MLGA) for the construction of clock binary tree. 1441-1445
  
• Yiyuan Gong, Morikazu Nakamura, Shiro Tamaki:
  Parallel genetic algorithms on line topology of heterogeneous computing resources. 1447-1454
  
• Jian-Hung Chen, Shinn-Ying Ho, David E. Goldberg:
  Quality-time analysis of multi-objective evolutionary algorithms. 1455-1462
  
• TeongJoo Ong, Ryan Saunders, John Keyser, John J. Leggett:
  Terrain generation using genetic algorithms. 1463-1470
  
• Chen-hsiung Chan, Sheng-An Lee, Cheng-Yan Kao, Huai-Kuang Tsai:
  Improving EAX with restricted 2-opt. 1471-1476
  
• Serkan Yilmaz, Kostadin Ivanov, Samuel Levine:
  Application of genetic algorithm to optimize burnable poison placement in pressurized water reactors. 1477-1483
  
• Naoki Mori, Masayuki Takeda, Keinosuke Matsumoto:
  A comparison study between genetic algorithms and bayesian optimize algorithms by novel indices. 1485-1492
  
• William Rand, Rick L. Riolo:
  The problem with a self-adaptative mutation rate in some environments: a case study using the shaky ladder hyperplane-defined functions. 1493-1500
  
• Zhao-hua Yang, Jian-cheng Fang, Zhen-qiang Qi:
  Flight midcourse guidance control based on genetic algorithm. 1501-1506
  
• Jacob G. Martin:
  Subproblem optimization by gene correlation with singular value decomposition. 1507-1514
  
• Yossi Borenstein, Riccardo Poli:
  Information landscapes. 1515-1522
  
• Matthew A. Russell, Gary B. Lamont:
  A genetic algorithm for unmanned aerial vehicle routing. 1523-1530
  
• Heni Ben Amor, Achim Rettinger:
  Intelligent exploration for genetic algorithms: using self-organizing maps in evolutionary computation. 1531-1538
  
• Dirk Thierens:
  An adaptive pursuit strategy for allocating operator probabilities. 1539-1546
  

Poster Session: Genetic algorithms

• Michael R. Peterson, Travis E. Doom, Michael L. Raymer:
  GA-facilitated classifier optimization with varying similarity measures. 1549-1550
  
• Michelle Lyman, Gary Lewandowski:
  Genetic programming for association rules on card sorting data. 1551-1552
  
• Anna Paszynska:
  An extension of vose's markov chain model for genetic algorithms. 1553-1554
  
• Zhigang Wang, Mustafizur Rahman, Yoke San Wong:
  Multi-niche crowding in the development of parallel genetic simulated annealing. 1555-1556
  
• Lam Thu Bui, Jürgen Branke, Hussein A. Abbass:
  Diversity as a selection pressure in dynamic environments. 1557-1558
  
• José Antonio Martin H.:
  Search space modulation in genetic algorithms: evolving the search space by sinusoidal transformations. 1559-1560
  
• Kei Ohnishi, Kaori Yoshida:
  Evolutionary change in developmental timing. 1561-1562
  
• Dana Vrajitoru, Jason DeBoni:
  Hybrid real-coded mutation for genetic algorithms applied to graph layouts. 1563-1564
  
• David M. Cherba, William F. Punch, Phil Duxbury, Simon Billinge, Pavol Juhas:
  Conformation of an ideal bucky ball molecule by genetic algorithm and geometric constraint from pair distance data: genetic algorithm. 1565-1566
  
• Surapong Auwatanamongkol:
  Inexact pattern matching using genetic algorithm. 1567-1568
  
• Lin Cong, Yuheng Sha, Licheng Jiao, Fang Liu:
  Directional self-learning of genetic algorithm. 1569-1570
  
• Cecília Reis, José António Tenreiro Machado, J. Boaventura Cunha:
  Fractional dynamic fitness functions for GA-based circuit design. 1571-1572
  
• Shin Ando, Shigenobu Kobayashi:
  Fitness-based neighbor selection for multimodal function optimization. 1573-1574
  
• Johan Berntsson, Maolin Tang:
  Adaptive sizing of populations and number of islands in distributed genetic algorithms. 1575-1576
  
• Jun Zhang, Henry Shu-Hung Chung, Jinghui Zhong:
  Adaptive crossover and mutation in genetic algorithms based on clustering technique. 1577-1578
  
• Johan Berntsson, Maolin Tang:
  Dynamic optimization of migration topology in internet-based distributed genetic algorithms. 1579-1580
  
• Jung Hwan Kim, Sung-Soon Choi, Byung Ro Moon:
  Normalization for neural network in genetic search. 1581-1582
  
• Chang Wook Ahn, Sanghoun Oh, Rudrapatna S. Ramakrishna:
  On the practical genetic algorithms. 1583-1584
  
• Sadiq M. Sait, Mohammed Faheemuddin, Mahmood R. Minhas, Syed Sanaullah:
  Multiobjective VLSI cell placement using distributed genetic algorithm. 1585-1586
  
• Edgardo Ferretti, Susana C. Esquivel:
  Knowledge insertion: an efficient approach to reduce effort in simple genetic algorithms for unrestricted parallel equal machines scheduling. 1587-1588
  
• Artem Sokolov, L. Darrell Whitley, Monte Lunacek:
  Alternative implementations of the Griewangk function. 1589-1590
  
• Pedro A. Diaz-Gomez, Dean F. Hougen:
  Analysis and mathematical justification of a fitness function used in an intrusion detection system. 1591-1592
  
• Pio Fenton, Paul Walsh:
  A comparison of messy GA and permutation based GA for job shop scheduling. 1593-1594
  
• Michael Affenzeller, Stefan Wagner, Stephan M. Winkler:
  Goal-oriented preservation of essential genetic information by offspring selection. 1595-1596
  
• Agustín León-Barranco, Sandra E. Barajas, Carlos A. Reyes García:
  ARGEN + AREPO: mixing the artificial genetic engineering and artificial evolution of populations to improve the search process. 1597-1598
  
• Frank W. Moore:
  A genetic algorithm for optimized reconstruction of quantized one-dimensional signals. 1599-1600
  
• Stephen Chen, Gregory Pitt:
  Isolating the benefits of respect. 1601-1602
  

Genetic programming

• Jason Stevens, Robert B. Heckendorn, Terence Soule:
  Exploiting disruption aversion to control code bloat. 1605-1612
  
• M. Collins:
  Finding needles in haystacks is harder with neutrality. 1613-1618
  
• Jianjun Hu, Xiwei Zhong, Erik D. Goodman:
  Open-ended robust design of analog filters using genetic programming. 1619-1626
  
• Jason M. Daida:
  Towards identifying populations that increase the likelihood of success in genetic programming. 1627-1634
  
• Christian Lasarczyk, Wolfgang Banzhaf:
  Total synthesis of algorithmic chemistries. 1635-1640
  
• Emily M. Zechman, S. Ranji Ranjithan:
  Multipopulation cooperative coevolutionary programming (MCCP) to enhance design innovation. 1641-1648
  
• James Alfred Walker, Julian Francis Miller:
  Investigating the performance of module acquisition in cartesian genetic programming. 1649-1656
  
• Paul Massey, John A. Clark, Susan Stepney:
  Evolution of a human-competitive quantum fourier transform algorithm using genetic programming. 1657-1663
  
• Ian Dempsey, Michael O'Neill, Anthony Brabazon:
  Meta-grammar constant creation with grammatical evolution by grammatical evolution. 1665-1671
  
• Sara Silva, Ernesto Costa:
  Resource-limited genetic programming: the dynamic approach. 1673-1680
  
• David Jackson:
  Parsing and translation of expressions by genetic programming. 1681-1688
  
• Lee Spector, Jon Klein, Maarten Keijzer:
  The Push3 execution stack and the evolution of control. 1689-1696
  
• Cezary Z. Janikow, Christopher J. Mann:
  CGP visits the Santa Fe trail: effects of heuristics on GP. 1697-1704
  
• Tadahiko Murata, Takashi Nakamura:
  Genetic network programming with automatically defined groups for assigning proper roles to multiple agents. 1705-1712
  
• Jason M. Daida, Michael E. Samples, Matthew J. Byom:
  Probing for limits to building block mixing with a tunably-difficult problem for genetic programming. 1713-1720
  
• Marc D. Richards, L. Darrell Whitley, J. Ross Beveridge, Todd Mytkowicz, Duong Nguyen, David Rome:
  Evolving cooperative strategies for UAV teams. 1721-1728
  
• Gregory Hornby:
  Measuring, enabling and comparing modularity, regularity and hierarchy in evolutionary design. 1729-1736
  
• James F. Smith III:
  Evolving fuzzy decision tree structure that adapts in real-time. 1737-1744
  
• David Jackson:
  Dormant program nodes and the efficiency of genetic programming. 1745-1751
  
• Rachel Cavill, Stephen L. Smith, Andrew M. Tyrrell:
  Multi-chromosomal genetic programming. 1753-1759
  
• Byoung-Tak Zhang, Ha-Young Jang:
  Molecular programming: evolving genetic programs in a test tube. 1761-1768
  

Poster Session: Genetic programming

• Sireesha Besetti, Terence Soule:
  Function choice, resiliency and growth in genetic programming. 1771-1772
  
• Hammad Majeed, Conor Ryan, R. Muhammad Atif Azad:
  Evaluating GP schema in context. 1773-1774
  
• Kohsuke Yanai, Hitoshi Iba:
  Probabilistic distribution models for EDA-based GP. 1775-1776
  
• Riccardo Poli, William B. Langdon:
  Backward-chaining genetic programming. 1777-1778
  
• Nate Foreman, Matthew P. Evett:
  Preventing overfitting in GP with canary functions. 1779-1780
  
• Nelishia Pillay:
  An investigation into using genetic programming as a means of inducing solutions to novice procedural programming problems. 1781-1782
  
• Sylvain Gelly, Olivier Teytaud, Nicolas Bredeche, Marc Schoenauer:
  A statistical learning theory approach of bloat. 1783-1784
  
• Radovan Ondas, Martin Pelikan, Kumara Sastry:
  Scalability of genetic programming and probabilistic incremental program evolution. 1785-1786
  
• Xiao Luo, Malcolm I. Heywood, A. Nur Zincir-Heywood:
  Evolving recurrent models using linear GP. 1787-1788
  
• Ján Antolík, William H. Hsu:
  Evolutionary tree genetic programming. 1789-1790
  
• Michael E. Samples, Jason M. Daida, Matthew J. Byom, Matt Pizzimenti:
  Parameter sweeps for exploring GP parameters. 1791-1792
  

Learning classifier systems and other genetics-based machine learning

• Daan Wierstra, Faustino J. Gomez, Jürgen Schmidhuber:
  Modeling systems with internal state using evolino. 1795-1802
  
• B. Ravichandran, Avinash Gandhe, Robert E. Smith:
  XCS for robust automatic target recognition. 1803-1810
  
• Leila Shila Shafti, Eduardo Pérez:
  Constructive induction and genetic algorithms for learning concepts with complex interaction. 1811-1818
  
• Drew Mellor:
  A first order logic classifier system. 1819-1826
  
• Pier Luca Lanzi, Daniele Loiacono, Stewart W. Wilson, David E. Goldberg:
  Extending XCSF beyond linear approximation. 1827-1834
  
• Martin V. Butz:
  Kernel-based, ellipsoidal conditions in the real-valued XCS classifier system. 1835-1842
  
• Jaume Bacardit:
  Analysis of the initialization stage of a Pittsburgh approach learning classifier system. 1843-1850
  
• Jan Drugowitsch, Alwyn Barry:
  XCS with eligibility traces. 1851-1858
  
• Pier Luca Lanzi, Daniele Loiacono, Stewart W. Wilson, David E. Goldberg:
  XCS with computed prediction in multistep environments. 1859-1866
  
• Samuel Landau, Olivier Sigaud, Marc Schoenauer:
  ATNoSFERES revisited. 1867-1874
  
• William N. L. Browne, Dan Scott:
  An abstraction agorithm for genetics-based reinforcement learning. 1875-1882
  
• Hai Huong Dam, Hussein A. Abbass, Chris Lokan:
  DXCS: an XCS system for distributed data mining. 1883-1890
  

Poster Session: Learning classifier systems and other genetics-based machine learning

• Xavier Llorà, Kumara Sastry, David E. Goldberg:
  The compact classifier system: motivation, analysis, and first results. 1993-1994
  

Real world applications

• M. Ihsan Ecemis, Eric Bonabeau, Trent Ashburn:
  Interactive estimation of agent-based financial markets models: modularity and learning. 1897-1904
  
• Julien Budynek, Eric Bonabeau, Ben Shargel:
  Evolving computer intrusion scripts for vulnerability assessment and log analysis. 1905-1912
  
• Yiu-Fai Sit, Risto Miikkulainen:
  Learning basic navigation for personal satellite assistant using neuroevolution. 1913-1920
  
• Deon Garrett, Joseph Vannucci, Rodrigo Silva, Dipankar Dasgupta, James Simien:
  Genetic algorithms for the sailor assignment problem. 1921-1928
  
• Jeffrey P. Ridder, Jason C. HandUber:
  Mission planning for joint suppression of enemy air defenses using a genetic algorithm. 1929-1936
  
• Lucas Bradstreet, Luigi Barone, R. Lyndon While:
  Map-labelling with a multi-objective evolutionary algorithm. 1937-1944
  
• Thomas Schlichter, Christian Haubelt, Jürgen Teich:
  Improving EA-based design space exploration by utilizing symbolic feasibility tests. 1945-1952
  
• John R. Koza, Sameer H. Al-Sakran, Lee W. Jones:
  Automated re-invention of six patented optical lens systems using genetic programming. 1953-1960
  
• Uli Grasemann, Risto Miikkulainen:
  Effective image compression using evolved wavelets. 1961-1968
  
• Eric-Wubbo Lameijer, Adriaan P. IJzerman, Joost N. Kok:
  The molecule evoluator: an interactive evolutionary algorithm for designing drug molecules. 1969-1976
  
• Kenneth O. Stanley, Nate Kohl, Rini Sherony, Risto Miikkulainen:
  Neuroevolution of an automobile crash warning system. 1977-1984
  
• Ingo Mierswa:
  Incorporating fuzzy knowledge into fitness: multiobjective evolutionary 3D design of process plants. 1985-1992
  
• David J. Montana, Jason Redi:
  Optimizing parameters of a mobile ad hoc network protocol with a genetic algorithm. 1993-1998
  
• Maarten Keijzer, Martin Baptist, Vladan Babovic, Javier Rodriguez Uthurburu:
  Determining equations for vegetation induced resistance using genetic programming. 1999-2006
  
• Rafal Kicinger, Tomasz Arciszewski, Kenneth A. De Jong:
  Parameterized versus generative representations in structural design: an empirical comparison. 2007-2014
  
• Daniel Stevens, Sanjoy Das, Balasubramaniam Natarajan:
  A multi-objective algorithm for DS-CDMA code design based on the clonal selection principle. 2015-2020
  
• Franz Rothlauf, Daniel Schunk, Jella Pfeiffer:
  Classification of human decision behavior: finding modular decision rules with genetic algorithms. 2021-2028
  
• Greg Lee, Vadim Bulitko:
  GAMM: genetic algorithms with meta-models for vision. 2029-2036
  
• Yoon-Seok Choi, Byung Ro Moon, Sang Yong Seo:
  Genetic fuzzy discretization with adaptive intervals for classification problems. 2037-2043
  
• Ju Han, Bir Bhanu:
  Hierarchical multi-sensor image registration using evolutionary computation. 2045-2052
  
• Bogdan Tomoyuki Nassu, Elias Procópio Duarte Jr., Aurora Trinidad Ramirez Pozo:
  A comparison of evolutionary algorithms for system-level diagnosis. 2053-2060
  
• Yung-Keun Kwon, Sung-Soon Choi, Byung Ro Moon:
  Stock prediction based on financial correlation. 2061-2066
  
• Garnett Carl Wilson, Malcolm I. Heywood:
  Use of a genetic algorithm in brill's transformation-based part-of-speech tagger. 2067-2073
  
• Jonathan Wight, Yi Zhang:
  An "ageing" operator and its use in the highly constrained topological optimization of HVAC system design. 2075-2082
  
• Barry Ahrens:
  Genetic algorithm optimization of superresolution parameters. 2083-2088
  
• Yung-Keun Kwon, Byung Ro Moon:
  Nonlinear feature extraction using a neuro genetic hybrid. 2089-2096
  
• Ashish Sureka, Peter R. Wurman:
  Applying metaheuristic techniques to search the space of bidding strategies in combinatorial auctions. 2097-2103
  
• Maoguo Gong, Ling Wang, Licheng Jiao, Haifeng Du:
  An artificial immune system algorithm for CDMA multiuser detection over multi-path channels. 2105-2111
  
• Emma Carter, Steve Ebdon, Clive Neal-Sturgess:
  Optimization of passenger car design for the mitigation of pedestrian head injury using a genetic algorithm. 2113-2120
  
• Samer L. Hijazi, Balasubramaniam Natarajan, Sanjoy Das:
  An ant colony algorithm for multi-user detection in wireless communication systems. 2121-2126
  
• Grant Cochenour, Jerad Simon, Sanjoy Das, Anil Pahwa, Surasish Nag:
  A pareto archive evolutionary strategy based radial basis function neural network training algorithm for failure rate prediction in overhead feeders. 2127-2132
  
• Jeremiah Nummela, Bryant A. Julstrom:
  Evolving petri nets to represent metabolic pathways. 2133-2139
  
• Bo Yuan, Marcus Gallagher, Stuart Crozier:
  MRI magnet design: search space analysis, EDAs and a real-world problem with significant dependencies. 2141-2148
  
• Sam Talaie, Ryan E. Leigh, Sushil J. Louis, Gary L. Raines:
  Predicting mining activity with parallel genetic algorithms. 2149-2155
  
• Swagatam Das, Amit Konar, Uday Kumar Chakraborty:
  An efficient evolutionary algorithm applied to the design of two-dimensional IIR filters. 2157-2163
  
• Andrea Soltoggio:
  An enhanced GA to improve the search process reliability in tuning of control systems. 2165-2172
  
• Martina Hasenjäger, Bernhard Sendhoff, Toyotaka Sonoda, Toshiyuki Arima:
  Three dimensional evolutionary aerodynamic design optimization with CMA-ES. 2173-2180
  
• Q. Tuan Pham:
  Evolutionary optimization of dynamic control problems accelerated by progressive step reduction. 2181-2187
  

Poster Session: Real world applications

• Fatih Alim, Kostadin Ivanov:
  Heuristic rules embedded genetic algorithm to solve in-core fuel management optimization problem. 2191-2192
  
• Ernesto Sánchez, Massimiliano Schillaci, Matteo Sonza Reorda, Giovanni Squillero, Luca Sterpone, Massimo Violante:
  New evolutionary techniques for test-program generation for complex microprocessor cores. 2193-2194
  
• Tomoyuki Hiroyasu, Mitsunori Miki, Seiichi Nakayama, Yoshiko Hanada:
  Multi-objective optimization of diesel engine emissions and fuel economy using SPEA2+. 2195-2196
  
• Keshav P. Dahal, Stuart J. Galloway, Graeme M. Burt, Jim R. McDonald, Ian Hopkins:
  A case study of process facility optimization using discrete event simulation and genetic algorithm. 2197-2198
  
• Sean R. Szumlanski, Annie S. Wu, Charles E. Hughes:
  Collaborative interactive evolution. 2199-2200
  
• Yuji Sato, Ryutaro Kanno:
  Event-driven learning classifier systems for online soccer games. 2201-2202
  
• P. Whiting, P. W. Poon, J. N. Carter:
  A genetic algorithm approach to the selection of near-optimal subsets from large sets. 2203-2204
  
• Ming-Hui Jin, Cheng-Yan Kao, Yu-Cheng Huang, D. Frank Hsu, Ren-Guey Lee, Chih-Kung Lee:
  Compact genetic algorithm for active interval scheduling in hierarchical sensor networks. 2205-2206
  
• Flor A. Castillo, Carlos M. Villa:
  Symbolic regression in multicollinearity problems. 2207-2208
  
• Mohammad I. Daoud, Nawwaf N. Kharma:
  GATS 1.0: a novel GA-based scheduling algorithm for task scheduling on heterogeneous processor nets. 2209-2210
  
• Timothy Meekhof, Robert B. Heckendorn:
  Using evolutionary optimization to improve Markov-based classification with limited training data. 2211-2212
  
• Richard O. Day, Abel S. Nunez, Gary B. Lamont:
  MOEA design of robust digital symbol sets. 2213-2214
  
• Kisung Seo, Erik D. Goodman, Ronald C. Rosenberg:
  Design of air pump system using bond graph and genetic programming method. 2215-2216
  
• Chihoon Lim, Eoksu Sim:
  Production planning in manufacturing/remanufacturing environment using genetic algorithm. 2217-2218
  
• Diego Sal Díaz, Manuel Graña Romay:
  Introducing a watermarking with a multi-objective genetic algorithm. 2219-2220
  
• Tiago A. E. Ferreira, Germano C. Vasconcelos, Paulo J. L. Adeodato:
  A new evolutionary method for time series forecasting. 2221-2222
  

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