GECCO 2011: Dublin, Ireland - Companion Material

• 
  Natalio Krasnogor, Pier Luca Lanzi:
  13th Annual Genetic and Evolutionary Computation Conference, GECCO 2011, Companion Material Proceedings, Dublin, Ireland, July 12-16, 2011. ACM 2011, ISBN 978-1-4503-0690-4

Ant colony optimization and swarm intelligence track posters

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  Richard D. Coates, Simon J. Hickinbotham:
  Estimating swarm parameters by evolutionary learning. 1-2
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  Arles Ernesto Rodríguez Portela, Jonatan Gómez Perdomo:
  Mechanism of failure diagnosis based on language games and q-learning over a termites simulator. 3-4
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  Tomasz M. Gwizdalla:
  Different versions of particle swarm optimization for magnetic problems. 5-6
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  Yijun Chen, Man Leung Wong:
  Optimizing stacking ensemble by an ant colony optimization approach. 7-8
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  Victor Ciesielski, Perry Barile:
  Animations rendered by braitenberg vehicles. 9-10
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  Samreen Umer, Adnan Ahmed Khan:
  Optimal relay station placement in cooperative networks using particle swarm. 11-12
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  Sabrina M. Oliveira, Mohamed Saifullah Hussin, Thomas Stützle, Andrea Roli, Marco Dorigo:
  A detailed analysis of the population-based ant colony optimization algorithm for the TSP and the QAP. 13-14
• 
  Ying Lin, Jun Zhang:
  An ant colony optimization approach for efficient admission scheduling of elective inpatients. 15-16
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  Tiago Amador Coelho, Ahmed Ali Abdalla Esmin, Wagner Meira Jr.:
  Particle swarm optimization for multi-label classification. 17-18

Artificial life/robotics/evolvable hardware track posters

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  Ivan Tanev, Tüze Kuyucu, Katsunori Shimohara:
  Incremental genetic programming via genetic transposition. 19-20
• 
  Kohei Nakajima, Tao Li, Naveen Kuppuswamy, Rolf Pfeifer:
  Biologically inspired control of a simulated octopus ARM via recurrent neural networks. 21-22
• 
  Daniel J. Couvertier, Philip K. McKinley:
  Effects of biased group selection on cooperative predation in digital organisms. 23-24
• 
  Jean-Marc Montanier, Nicolas Bredèche:
  Emergence of altruism in open-ended evolution in a population of autonomous agents. 25-26
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  A. E. Eiben, N. Ferreira, Martijn C. Schut, Serge Kernbach:
  Embodied artificial evolution: the future of artificial evolutionary systems. 27-28
• 
  Jaimie Murdock, Larry S. Yaeger:
  Genetic clustering for the identification of species. 29-30
• 
  Jason Yosinski, Jeff Clune, Diana Hidalgo, Sarah Nguyen, Juan Cristóbal Zagal, Hod Lipson:
  Generating gaits for physical quadruped robots: evolved neural networks vs. local parameterized search. 31-32

Bioinformatics, computational, systems, and synthetic biology track posters

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  Theodore W. Cornforth, Jim Tørresen, Hod Lipson:
  Ion channel modeling with analog circuit evolution. 33-34
• 
  Kristopher Hoover, Rachel Marceau, Tyndall Harris, Nicholas E. Hardison, David M. Reif, Alison A. Motsinger-Reif:
  Optimization of grammatical evolution decision trees. 35-36

Digital entertainment technologies and arts track posters

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  Denis Pallez, Andrea Tettamanzi, Célia da Costa Pereira:
  Comparing paired comparison-based interactive DE and tournament interactive GA on stained glass design. 37-38
• 
  Eduardo Vázquez-Fernández, Carlos Artemio Coello Coello, Feliu Davino Sagols Troncoso:
  An adaptive evolutionary algorithm based on typical chess problems for tuning a chess evaluation function. 39-40
• 
  Johannes H. Jensen, Pauline C. Haddow:
  Evolutionary music composition based on Zipf's law. 41-42
• 
  Jonathan Byrne, Erik Hemberg, Michael O'Neill:
  Interactive operators for evolutionary architectural design. 43-44

Evolutionary combinatorial optimization and metaheuristics track posters

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  Chan Hou Che, Zizhen Zhang, Andrew Lim:
  A memetic algorithm for solving multiperiod vehicle routing problem with profit. 45-46
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  Christian Grimme, Markus Kemmerling, Joachim Lepping:
  An expertise-guided multi-criteria approach to scheduling problems. 47-48
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  Santiago Enrique Conant-Pablos, Halley Jarumy Ferrer-Soriano, Hugo Terashima-Marín:
  Evolving solutions of mixed-model assembly line balancing problems by chaining heuristic optimization methods: track: evolutionary combinatorial optimization and meta-heuristics. 49-50
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  Wolfgang Steitz, Franz Rothlauf:
  Guided local search for the optimal communication spanning tree problem. 51-52
• 
  A. K. Qin, Florence Forbes:
  Dynamic regional harmony search with opposition and local learning. 53-54
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  Yao-Hsin Chou, Chia-Hui Chiu, Yi-Jyuan Yang:
  Quantum-inspired tabu search algorithm for solving 0/1 knapsack problems. 55-56
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  Luis de Marcos, Antonio García-Cabot, Eva García, José-Amelio Medina, Salvador Otón:
  Comparing the performance of evolutionary algorithms for permutation constraint satisfaction. 57-58
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  Saúl Domínguez-Isidro, Efrén Mezura-Montes, Luis Guillermo Osorio-Hernández:
  Addition chain length minimization with evolutionary programming. 59-60

Estimation of distribution algorithms track posters

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  Jen-Hao Chang, Chung-Hsiang Hsueh, Hsuan Lee, Tian-Li Yu, Tsung-Yu Ho:
  A test function with full controllability over overlapping: estimation of distribution algorithms. 61-62
• 
  Takayuki Higo:
  Importance sampling regularization for estimation of distribution algorithms. 63-64
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  David Wallin, Conor Ryan, R. Muhammad Atif Azad:
  Candidate oversampling prefers two to tango: estimation of distribution algorithms. 65-66
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  Warin Wattanapornprom, Prabhas Chongstitvatana:
  Solving multimodal combinatorial puzzles with edge-based estimation of distribution algorithm. 67-68
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  Ignacio Segovia-Dominguez, Arturo Hernández Aguirre, Enrique Raúl Villa Diharce:
  The gaussian polytree EDA for global optimization. 69-70
• 
  Kai-Chun Fan, Tian-Li Yu, Jui-Ting Lee:
  Interaction detection by NFE estimation: a practical view of building blocks. 71-72
• 
  Elham Salehi, Robin Gras:
  Efficient EDA for large opimization problems via constraining the search space of models. 73-74

Evolutionary multiobjective optimization track posters

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  Wali Khan Mashwani:
  Integration of NSGA-II and MOEA/D in multimethod search approach: algorithms. 75-76
• 
  Jingxuan Wei, Mengjie Zhang:
  Attraction based PSO with sphere search for dynamic constrained multi-objective optimization problems. 77-78
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  Martin Pilát, Roman Neruda:
  LAMM-MMA: multiobjective memetic algorithm with local aggregate meta-model. 79-80
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  Bing Wu, Weihua Sun, Yoshihiro Murata, Keiichi Yasumoto, Minoru Ito:
  A stamina-aware sightseeing tour scheduling method. 81-82
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  Javier H. López, Laura Lanzarini, Armando De Giusti:
  Evolutionary multiobjective optimization for emergency medical services. 83-84
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  Jingjing Ma, Yanhui Wang, Maoguo Gong, Licheng Jiao, Qingfu Zhang:
  Spatio-temporal data evolutionary clustering based on MOEA/D. 85-86
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  Stefano Suardi, Rajkumar Roy, Jörn Mehnen, Yoseph Tafesse Azene:
  Uncertainty based evolutionary optimisation. 87-88
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  Alexander E. I. Brownlee, Jonathan A. Wright, Monjur M. Mourshed:
  A multi-objective window optimisation problem. 89-90
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  Roberto Santana, Hossein Karshenas, Concha Bielza, Pedro Larrañaga:
  Quantitative genetics in multi-objective optimization algorithms: from useful insights to effective methods. 91-92
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  Rupesh Tulshyan, Kalyanmoy Deb, Sunith Bandaru:
  KKT proximity measure for testing convergence in smooth multi-objective optimization. 93-94
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  Noura Al Moubayed, Andrei Petrovski, John A. W. McCall:
  Clustering based leaders' selection in multi-objective evolutionary algorithms. 95-96
• 
  Adam Mostafa Ghandar, Zbigniew Michalewicz:
  Considerations of the nature of the relationship between generalization and interpretability in evolutionary fuzzy systems. 97-98
• 
  Ke Li, Sam Kwong, Kim-Fung Man:
  JGBL paradigm: a novel strategy to enhance the exploration ability of nsga-ii. 99-100
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  Marcos Luiz de Paula Bueno, Gina Maira Barbosa de Oliveira:
  Adaptive shifting of auxiliary strategies over three formulations of multicast routing problem. 101-102
• 
  Wenping Zou, Yunlong Zhu, Hanning Chen, Hai Shen:
  A novel multi-objective optimization algorithm based on artificial bee colony. 103-104
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  Alexandru-Adrian Tantar, Emilia Tantar, Pascal Bouvry:
  A classification of dynamic multi-objective optimization problems. 105-106
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  David J. Walker, Richard M. Everson, Jonathan E. Fieldsend:
  Rank-based dimension reduction for many-criteria populations. 107-108
• 
  Christian Grimme, Joachim Lepping:
  Integrating niching into the predator-prey model using epsilon-constraints. 109-110

Evolution strategies and evolutionary programming track posters

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  Wenyin Gong, Zhihua Cai:
  Adaptive parameter selection for strategy adaptation in differential evolution. 111-112
• 
  José Luis Guerrero, Antonio Berlanga, José Manuel Molina:
  A robust memetic algorithm with self-stopping capabilities. 113-114
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  Alfredo Cuesta-Infante, José Ignacio Hidalgo, María Victoria Rivas:
  (1+2)-evolution strategy for fitting a straight shuffle of min to a dataset. 115-116
• 
  Amine M. Boumaza:
  Designing artificial tetris players with evolution strategies and racing. 117-118
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  Thomas Bartz-Beielstein, Martina Friese, Martin Zaefferer, Boris Naujoks, Oliver Flasch, Wolfgang Konen, Patrick Koch:
  Noisy optimization with sequential parameter optimization and optimal computational budget allocation. 119-120

Genetic algorithms track posters

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  Maksud Ibrahimov, Arvind Mohais, Sven Schellenberg, Zbigniew Michalewicz:
  Comparison of cooperative, multiobjective cooperative and classical evolutionary algorithms for global supply chain optimisation. 121-122
• 
  Josh L. Wilkerson, Daniel R. Tauritz:
  A guide for fitness function design. 123-124
• 
  Mitsukuni Matayoshi:
  A new packing method for two dimensional rectilinear polygons using genetic algorithm. 125-126
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  Crown Guan Wang, Degang Wu, Wenjin Chen, Kwok Yip Szeto:
  Importance of information exchange in quasi-parallel genetic algorithms. 127-128
• 
  Lee Spector, Thomas Helmuth, Kyle Ira Harrington:
  Fecundity and selectivity in evolutionary computation. 129-130
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  Marcelo Beckmann, Beatriz S. L. P. de Lima, Nelson F. F. Ebecken:
  Genetic algorithms as a pre processing strategy for imbalanced datasets. 131-132
• 
  Alberto Moraglio, Yong-Hyuk Kim, Yourim Yoon:
  Geometric surrogate-based optimisation for permutation-based problems. 133-134
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  Eddy Parkinson, Adam Ghandar, Zbigniew Michalewicz, Andrew Tuson:
  Controlling the tradeoff between time and quality by considering the reproductive potential of offspring. 135-136
• 
  Telma Woerle de Lima, Alexandre Cláudio Botazzo Delbem, Franz Rothlauf:
  Analysis of properties of recombination operators proposed for the node-depth encoding. 137-138
• 
  Badarch Tserenchimed, Shu Liu, Hitoshi Iba:
  A trading method in FX using evolutionary algorithms: extensions based on reverse trend and settlement timing. 139-140
• 
  Min Shi:
  Empirical analysis of cooperative coevolution using blind decomposition. 141-142
• 
  Ming Yang, Zhihua Cai, Jing Guan, Wenyin Gong:
  Differential evolution with improved population reduction. 143-144
• 
  Evelyne Lutton, Jean-Daniel Fekete:
  Visual analytics of EA data. 145-146
• 
  Timothy Meekhof, Terence Soule:
  Noise, fitness distribution, and selection intensity in genetic algorithms. 147-148
• 
  Gene I. Sher:
  DXNN: evolving complex organisms in complex environments using a novel tweann system. 149-150
• 
  Sean Luke, Keith Sullivan, Faisal Abidi:
  Large scale empirical analysis of cooperative coevolution. 151-152
• 
  António Manuel Rodrigues Manso, Luís Miguel Parreira Correia:
  A multiset genetic algorithm for real coded problems. 153-154
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  Brian W. Goldman, Daniel R. Tauritz:
  Meta-evolved empirical evidence of the effectiveness of dynamic parameters. 155-156
• 
  Yu-Min Son, Byung Ro Moon:
  Raising mutation rate in the context of hybrid genetic algorithms. 157-158
• 
  Jing-Hui Zhong, Jun Zhang:
  A multi-objective memetic algorithm for relay node placement in wireless sensor network. 159-160
• 
  Mauro Castelli, Luca Manzoni, Leonardo Vanneschi:
  The effect of selection from old populations in genetic algorithms. 161-162

Genetics based machine learning track posters

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  Juan Peralta Donate, Paulo Cortez, Araceli Sanchis de Miguel, Germán Gutiérrez Sánchez:
  Evolving time-lagged feedforward neural networks for time series forecasting. 163-164
• 
  Kaoru Shimada, Kotaro Hirasawa:
  Evolving associative classifier for incomplete database using genetic network programming. 165-166
• 
  Richard Preen, Larry Bull:
  Fuzzy dynamical genetic programming in XCSF. 167-168
• 
  Daniele Loiacono:
  Fast prediction computation in learning classifier systems using CUDA. 169-170
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  Rita Castillo-Ortega, Nicolás Marín, Daniel Sánchez, Andrea Tettamanzi:
  A multi-objective memetic algorithm for the linguistic summarization of time series. 171-172
• 
  Claudio De Stefano, Gianluigi Folino, Francesco Fontanella, Alessandra Scotto di Freca:
  Using bayesian networks for selecting classifiers in GP ensembles. 173-174
• 
  Leonardo Trujillo, Yuliana Martínez, Patricia Melin:
  How many neurons?: a genetic programming answer. 175-176
• 
  Scott Niekum, Lee Spector, Andrew G. Barto:
  Evolution of reward functions for reinforcement learning. 177-178
• 
  Fengming Ye, Shingo Mabu, Kotaro Hirasawa:
  A memory scheme for genetic network programming with adaptive mutation. 179-180
• 
  Ignas Kukenys, Will N. Browne, Mengjie Zhang:
  Confusion matrices for improving performance of feature pattern classifier systems. 181-182

Genetic programming track posters

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  David Fagan, Miguel Nicolau, Erik Hemberg, Michael O'Neill, Anthony Brabazon:
  Dynamic ant: introducing a new benchmark for genetic programming in dynamic environments. 183-184
• 
  Glen D. Rodriguez Rafael, Carlos Javier Solano Salinas:
  Empirical study of surrogate models for black box optimizations obtained using symbolic regression via genetic programming. 185-186
• 
  Marc-André Gardner, Christian Gagné, Marc Parizeau:
  Bloat control in genetic programming with a histogram-based accept-reject method. 187-188
• 
  Carlos Iván Camargo Bareño, Cesar Augusto Pedraza Bonilla, Luis Fernado Niño, José Ignacio Martinez Torre:
  Intrinsic evolvable hardware for combinatorial synthesis based on SoC+FPGA and GPU platforms. 189-190
• 
  Michael O'Neill, Miguel Nicolau, Anthony Brabazon:
  Dynamic environments can speed up evolution with genetic programming. 191-192
• 
  Douglas Adriano Augusto, Helio J. C. Barbosa, André da Motta Salles Barreto, Heder S. Bernardino:
  A new approach for generating numerical constants in grammatical evolution. 193-194
• 
  Stephan M. Winkler, Michael Affenzeller, Stefan Wagner:
  Analysis of the effects of enhanced selection concepts for genetic programming based structure identification using fine-grained population diversity estimation. 195-196
• 
  Simon Harding, Julian F. Miller, Wolfgang Banzhaf:
  SMCGP2: finding algorithms that approximate numerical constants using quaternions and complex numbers. 197-198
• 
  Alexandros Agapitos, Michael O'Neill, Anthony Brabazon:
  Stateful program representations for evolving technical trading rules. 199-200
• 
  Carlton Downey, Mengjie Zhang:
  Caching for parallel linear genetic programming. 201-202
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  Clíodhna Tuite, Alexandros Agapitos, Michael O'Neill, Anthony Brabazon:
  Early stopping criteria to counteract overfitting in genetic programming. 203-204
• 
  William B. Langdon:
  Generalisation in genetic programming. 205-206

Generative and developmental systems track posters

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  Terence Soule, Robert B. Heckendorn:
  Developmental scalable hierarchies for multi-agent swarms. 207-208
• 
  Robin Harper:
  Dynamic l-systems in GE. 209-210

Parallel evolutionary systems track posters

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  Zhi-hui Zhan, Jun Zhang:
  Co-evolutionary differential evolution with dynamic population size and adaptive migration strategy. 211-212
• 
  Juan Porta, Jorge Parapar, Guillermo L. Taboada, Ramon Doallo, Francisco F. Rivera, Inés Santé, Marcos Suárez, Marcos Boullón, Rafael Crecente:
  A Java-based parallel genetic algorithm for the land use planning problem. 213-214

Real world applications track posters

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  Abhinav Malhotra, Varun Aggarwal:
  HIER-HEIR: an evolutionary system with hierarchical representation & contextual operators applied to fashion design. 215-216
• 
  Jeong-min Yu, Sang-Goog Lee, Moongu Jeon:
  Medical image segmentation by hybridizing ant colony optimization and fuzzy clustering algorithm. 217-218
• 
  Juan Peralta Donate, Paulo Cortez, Araceli Sanchis de Miguel, Germán Gutiérrez Sánchez:
  Evolving sparsely connected neural networks for multi-step ahead forecasting. 219-220
• 
  Andy Song, Feng Xie:
  Evolving automatic frame splitters. 221-222
• 
  Adam S. Banzi, Aurora T. R. Pozo, Elias Procópio Duarte Jr.:
  Bio-inspired event dissemination in dynamic and decentralized networks. 223-224
• 
  Ernesto Sánchez, Giovanni Squillero, Alberto Paolo Tonda:
  Evolutionary failing-test generation for modern microprocessors. 225-226
• 
  Eva Besada-Portas, Luis de la Torre, Alejandro Moreno, José Luis Risco-Martín:
  Performance analysis of multiobjective bio-inspired UAV path planners. 227-228
• 
  Ronald Hochreiter, Christoph Waldhauser:
  Evolved election forecasts: using genetic algorithms in improving election forecast results. 229-230
• 
  Forrest Stonedahl, David Anderson, William Rand:
  When does simulated data match real data? 231-232
• 
  Lydia Boudjeloud, Hanane Azzag:
  A cooperative biomimetic approach for high dimensional data mining. 233-234
• 
  Subhrajit Roy, Sk. Minhazul Islam, Saurav Ghosh, Swagatam Das, Ajith Abraham, Pavel Krömer:
  A modified differential evolution for autonomous deployment and localization of sensor nodes. 235-236
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  Paul Anton Letnes, Ingar Stian Nerbø, Lars Martin Sandvik Aas, Pål Gunnar Ellingsen, Morten Kildemo:
  Genetic invention of fast and optimal broad-band stokes/mueller polarimeter designs. 237-238
• 
  Victor Parque, Shingo Mabu, Kotaro Hirasawa:
  Genetic network programming with changing structures for a novel stock selection model. 239-240

Search-based software engineering track posters

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  José del Sagrado, Isabel María del Águila, Francisco Javier Orellana:
  Requirements interaction in the next release problem. 241-242
• 
  Josh L. Wilkerson, Daniel R. Tauritz:
  Scalability of the coevolutionary automated software correction system. 243-244
• 
  Martin Faunes, Marouane Kessentini, Houari A. Sahraoui:
  Software clustering by example. 245-246
• 
  Mike Papadakis, Nicos Malevris:
  Automatic mutation based test data generation. 247-248
• 
  Outi Räihä, Kai Koskimies, Erkki Mäkinen:
  Multi-objective genetic synthesis of software architecture. 249-250
• 
  Sebastian Bauersfeld, Stefan Wappler, Joachim Wegener:
  An approach to automatic input sequence generation for GUI testing using ant colony optimization. 251-252

Self-* search track posters

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  Mikdam Turkey, Riccardo Poli:
  Social adaptive groups: a new approach for evolutionary optimisation based on social behaviour evolution. 253-254
• 
  José Carlos Ortiz-Bayliss, Hugo Terashima-Marín, Ender Özcan, Andrew J. Parkes:
  On the idea of evolving decision matrix hyper-heuristics for solving constraint satisfaction problems. 255-256
• 
  Eunice López-Camacho, Hugo Terashima-Marín, Peter Ross:
  A hyper-heuristic for solving one and two-dimensional bin packing problems. 257-258
• 
  Mátyás Brendel, Marc Schoenauer:
  Instance-based parameter tuning for evolutionary AI planning. 259-260
• 
  José Carlos Ortiz-Bayliss, Hugo Terashima-Marín, Peter Ross, Santiago Enrique Conant-Pablos:
  Evolution of neural networks topologies and learning parameters to produce hyper-heuristics for constraint satisfaction problems. 261-262
• 
  Jürgen Branke, Jawad Elomari:
  Simultaneous tuning of metaheuristic parameters for various computing budgets. 263-264

Theory track posters

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  Chao Qian, Yang Yu, Zhi-Hua Zhou:
  Collisions are helpful for computing unique input-output sequences. 265-266
• 
  Marc Schoenauer, Fabien Teytaud, Olivier Teytaud:
  Simple tools for multimodal optimization. 267-268
• 
  Selmar K. Smit, Zoltán Szlávik, Ágoston E. Eiben:
  Population diversity index: a new measure for population diversity. 269-270

Evolutionary computation in practice

• 
  Ian Cox:
  Exploring opportunity spaces efficiently for fun and profit. 271-284

Evolutionary computation techniques for constraint handling

• 
  Donagh Hatton, Diarmuid P. O'Donoghue:
  Explorations on template-directed genetic repair using ancient ancestors and other templates. 325-332
• 
  Martin Holena, David Linke, Lukás Bajer:
  Case study: constraint handling in evolutionary optimization of catalytic materials. 333-340
• 
  Antonio Fernández, Consolación Gil, Antonio López Márquez, Raul Baños, Maria Dolores Gil Montoya, María Concepción Parra:
  A memetic algorithm for two-dimensional multi-objective bin-packing with constraints. 341-346
• 
  Xue-Feng Zhang, Miyuki Koshimura, Hiroshi Fujita, Ryuzo Hasegawa:
  Combining PSO and local search to solve scheduling problems. 347-354

Fourteenth international workshop on learning classifier systems

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  Kaveh Ahmadi Abhari, Ali Hamzeh, Sattar Hashemi:
  Voting based learning classifier system for multi-label classification. 355-360
• 
  Mohammad Behdad, Tim French, Luigi Barone, Mohammed Bennamoun:
  PCA for improving the performance of XCSF in classification of high-dimensional problems. 361-368
• 
  Ryan J. Urbanowicz, Nicholas A. Sinnott-Armstrong, Jason H. Moore:
  Random artificial incorporation of noise in a learning classifier system environment. 369-374
• 
  Muhammad Iqbal, Mengjie Zhang, Will N. Browne:
  Automatically defined functions for learning classifier systems. 375-382
• 
  Martin V. Butz, Olivier Sigaud:
  XCSF with local deletion: preventing detrimental forgetting. 383-390
• 
  Manuel Filipe Santos, Wesley Mathew, Henrique M. Dinis Santos:
  Grid data mining by means of learning classifier systems and distributed model induction. 391-398

Computational intelligence on consumer games and graphics hardware (CIGPU)

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  Leandro F. Cupertino, Cleomar Pereira da Silva, Douglas Mota Dias, Marco Aurélio Cavalcanti Pacheco, Cristiana Bentes:
  Evolving CUDA PTX programs by quantum inspired linear genetic programming. 399-406
• 
  Yuji Sato, Naohiro Hasegawa, Mikiko Sato:
  Acceleration of genetic algorithms for sudoku solution on many-core processors. 407-414
• 
  William B. Langdon:
  Debugging CUDA. 415-422
• 
  William B. Langdon:
  Performing with CUDA. 423-430
• 
  Petr Pospichal, Eoin Murphy, Michael O'Neill, Josef Schwarz, Jirí Jaros:
  Acceleration of grammatical evolution using graphics processing units: computational intelligence on consumer games and graphics hardware. 431-438
• 
  Martín Pedemonte, Enrique Alba, Francisco Luna:
  Bitwise operations for GPU implementation of genetic algorithms. 439-446
• 
  Tony E. Lewis, George D. Magoulas:
  Identifying similarities in TMBL programs with alignment to quicken their compilation for GPUs: computational intelligence on consumer games and graphics hardware. 447-454
• 
  Tony E. Lewis, George D. Magoulas:
  TMBL kernels for CUDA GPUs compile faster using PTX: computational intelligence on consumer games and graphics hardware. 455-462
• 
  Simon Harding, Wolfgang Banzhaf:
  Implementing cartesian genetic programming classifiers on graphics processing units using GPU.NET. 463-470

Medical applications of genetic and evolutionary computation (MedGEC)

• 
  Harold Soh, Yiannis Demiris:
  Multi-reward policies for medical applications: anthrax attacks and smart wheelchairs. 471-478
• 
  Manuel Cruz-Ramírez, Juan Carlos Fernández Caballero, Francisco Fernández-Navarro, Javier Briceño, Manuel de la Mata, César Hervás-Martínez:
  Memetic evolutionary multi-objective neural network classifier to predict graft survival in liver transplant patients. 479-486
• 
  Roberto Ugolotti, Pablo Mesejo, Stefano Cagnoni, Mario Giacobini, Ferdinando Di Cunto:
  Automatic hippocampus localization in histological images using PSO-based deformable models. 487-494
• 
  Satchidananda Dehuri, Rahul Roy, Sung-Bae Cho:
  An adaptive binary PSO to learn bayesian classifier for prognostic modeling of metabolic syndrome. 495-502
• 
  Stephan M. Winkler, Michael Affenzeller, Witold Jacak, Herbert Stekel:
  Identification of cancer diagnosis estimation models using evolutionary algorithms: a case study for breast cancer, melanoma, and cancer in the respiratory system. 503-510
• 
  Viktoria Dorfer, Stephan M. Winkler, Thomas Kern, Sophie A. Blank, Gerald Petz, Patrizia Faschang:
  On the performance of evolutionary algorithms in biomedical keyword clustering. 511-518

Evolutionary computation and multi-agent systems and simulation (ECoMASS) - fifth annual workshop

• 
  Syed Md. Galib, Irene Moser:
  Road traffic optimisation using an evolutionary game. 519-526
• 
  Mikdam Turkey, Riccardo Poli:
  A social behaviour evolution approach for evolutionary optimisation. 527-534
• 
  Gideon M. Gluckman, Joanna Bryson:
  An agent-based model of the effects of a primate social structure on the speed of natural selection. 535-542
• 
  M. Ehsan Shafiee, Emily M. Zechman:
  Sociotechnical simulation and evolutionary algorithm optimization for routing siren vehicles in a water distribution contamination event. 543-550
• 
  Robert Junges, Franziska Klügl:
  Evolution for modeling: a genetic programming framework for sesam. 551-558
• 
  Wei Guo, Wolfgang Jank, William Rand:
  Estimating functional agent-based models: an application to bid shading in online markets format. 559-566

1st workshop on evolutionary computation for designing generic algorithms

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  Rodrigo C. Barros, Márcio P. Basgalupp, André Carlos Ponce Leon Ferreira de Carvalho, Alex Alves Freitas:
  Towards the automatic design of decision tree induction algorithms. 567-574
• 
  Brian W. Goldman, Daniel R. Tauritz:
  Self-configuring crossover. 575-582
• 
  John Robert Woodward, Jerry Swan:
  Automatically designing selection heuristics. 583-590
• 
  Mátyás Brendel, Marc Schoenauer:
  Instance-based parameter tuning for evolutionary AI planning. 591-598

Bio-inspired solutions for wireless sensor networks (GECCO BIS-WSN 2011)

• 
  Giovanni Comarela, Kênia Carolina Gonçalves, Gisele Lobo Pappa, Jussara M. Almeida, Virgílio A. F. Almeida:
  Robot routing in sparse wireless sensor networks with continuous ant colony optimization. 599-606
• 
  André Siqueira Ruela, André Luiz Lins de Aquino, Frederico Gadelha Guimarães:
  A cooperative coevolutionary algorithm for the design of wireless sensor networks: track name: bio-inspired solutions for wireless sensor networks. 607-614
• 
  Hugo Hernández, Christian Blum:
  Implementing a model of Japanese tree frogs' calling behavior in sensor networks: a study of possible improvements. 615-622

3rd symbolic regression and modeling workshop for GECCO 2011

• 
  Sean Stijven, Wouter Minnebo, Katya Vladislavleva:
  Separating the wheat from the chaff: on feature selection and feature importance in regression random forests and symbolic regression. 623-630
• 
  Gabriel Kronberger, Michael Kommenda, Michael Affenzeller:
  Overfitting detection and adaptive covariant parsimony pressure for symbolic regression. 631-638
• 
  Erik Hemberg, Lester T. W. Ho, Michael O'Neill, Holger Claussen:
  A symbolic regression approach to manage femtocell coverage using grammatical genetic programming. 639-646
• 
  Luis M. Torres-Treviño:
  Symbolic regression using α- β operators and estimation of distribution algorithms: preliminary results. 647-654
• 
  Kenneth L. Holladay, John Marshall Sharp, Marc Janssens:
  Automatic pyrolysis mass loss modeling from thermo-gravimetric analysis data using genetic programming. 655-662

Optimization by building and using probabilistic models (OBUPM-2011)

• 
  Peter A. N. Bosman, Dirk Thierens:
  The roles of local search, model building and optimal mixing in evolutionary algorithms from a bbo perspective. 663-670
• 
  Cezary Z. Janikow, John W. Aleshunas, Mark Hauschild:
  Second order heuristics in ACGP. 671-678
• 
  Roberto Santana:
  Estimation of distribution algorithms: from available implementations to potential developments. 679-686

Scaling behaviours of landscapes, parameters and algorithms

• 
  Valentino Santucci, Alfredo Milani:
  Covariance-based parameters adaptation in differential evolution. 687-690
• 
  Carolina Salto, Enrique Alba, Francisco Luna:
  Using landscape measures for the online tuning of heterogeneous distributed gas. 691-694
• 
  Pilar Caamaño, José Antonio Becerra, Francisco Bellas, Richard J. Duro:
  Are evolutionary algorithm competitions characterizing landscapes appropriately. 695-702
• 
  Tianjun Liao, Marco Antonio Montes de Oca, Thomas Stützle:
  Tuning parameters across mixed dimensional instances: a performance scalability study of Sep-G-CMA-ES. 703-706
• 
  David Corne, Alan P. Reynolds:
  Evaluating optimization algorithms: bounds on the performance of optimizers on unseen problems. 707-710

GreenIT evolutionary computation

• 
  Consolación Gil, Pedro Sánchez, Francisco G. Montoya, Antonio López Márquez:
  Open source tool for energy saving and efficient system management. 711-718
• 
  Jamal Toutouh, Enrique Alba:
  An efficient routing protocol for green communications in vehicular ad-hoc networks. 719-726
• 
  Álvaro Fialho, Youssef Hamadi, Marc Schoenauer:
  Optimizing architectural and structural aspects of buildings towards higher energy efficiency. 727-732
• 
  Alexandru-Adrian Tantar, Emilia Tantar, Pascal Bouvry:
  Load balancing for sustainable ICT. 733-738

Graduate students workshop

• 
  Amit Benbassat, Moshe Sipper:
  Evolving board-game players with genetic programming. 739-742
• 
  Anke Endler, Martin V. Butz, Günter Daniel Rey:
  Extracting adaptation strategies for e-learning programs with XCS. 743-746
• 
  Mikdam Turkey, Riccardo Poli:
  Investigating a new paradigm for designing evolutionary optimisation algorithms using social behaviour evolution. 747-750
• 
  Erik Dovgan, Matjaz Gams, Bogdan Filipic:
  A multiobjective optimization algorithm for discovering driving strategies. 751-754
• 
  Armen Kherlopian, Francis A. Ortega, David J. Christini:
  Cardiac myocyte model parameter sensitivity analysis and model transformation using a genetic algorithm. 755-758
• 
  Fedor Tsarev, Kirill Egorov:
  Finite state machine induction using genetic algorithm based on testing and model checking. 759-762
• 
  Maxim Buzdalov:
  Generation of tests for programming challenge tasks using evolution algorithms. 763-766
• 
  Stefano Nichele:
  Discrete dynamics of cellular machines: specification and interpretation. 767-770
• 
  Saúl Zapotecas Martínez, Carlos A. Coello Coello:
  Swarm intelligence guided by multi-objective mathematical programming techniques. 771-774
• 
  Anton Alexandrov, Alexey A. Sergushichev, Sergey Kazakov, Fedor Tsarev:
  Genetic algorithm for induction of finite automata with continuous and discrete output actions. 775-778
• 
  Eoin Murphy:
  Examining grammars and grammatical evolution in dynamic environments. 779-782
• 
  David Fagan:
  Genotype-phenotype mapping in dynamic environments with grammatical evolution. 783-786
• 
  Sunith Bandaru, Kalyanmoy Deb:
  Design knowledge extraction in multi-objective optimization problems. 787-790
• 
  António Manuel R. Manso, Luís Miguel P. Correia:
  MuGA: multiset genetic algorithm. 791-794
• 
  Rogelio Salinas-Gutiérrez, Arturo Hernández Aguirre, Enrique Raúl Villa Diharce:
  Estimation of distribution algorithms based on copula functions. 795-798
• 
  Thomas Helmuth, Lee Spector, Brian Martin:
  Size-based tournaments for node selection. 799-802

Late breaking abstracts workshop

• 
  Zann Gill:
  Collaborative intelligence in living systems: algorithmic implications of evo-devo debates. 803-804
• 
  Emily M. Zechman, Marcio H. Giacomoni, M. Ehsan Shafiee:
  A multi-objective niching co-evolutionary algorithm (MNCA) for identifying diverse sets of non-dominated solutions. 805-806
• 
  David Andrew Cape, Daniel R. Tauritz:
  Probabilistically interpolated rational hypercube landscape evolutionary algorithm. 807-808
• 
  Sameer Kumar Singh, Ruppa K. Thulasiram, Parimala Thulasiraman:
  Pricing transmission rights using ant colony optimization. 809-810
• 
  Stephen Chen, James Montgomery:
  A simple strategy to maintain diversity and reduce crowding in particle swarm optimization. 811-812
• 
  Cem Celal Tutum, Zhun Fan:
  Automatic synthesis of MEMS devices using self-adaptive hybrid metaheuristics. 813-814
• 
  Olivier Regnier-Coudert, John A. W. McCall:
  Privacy-preserving approach to bayesian network structure learning from distributed data. 815-816
• 
  Sylvain Koos, Jean-Baptiste Mouret:
  Online adaptation of locomotion with evolutionary algorithms: a transferability-based approach. 817-818
• 
  José Pinto, Rui Ferreira Neves, Nuno Horta:
  Fitness function evaluation for MA trading strategies based on genetic algorithms. 819-820
• 
  Lisa Jing Yan, Nick Cercone:
  Bayesian networks learning for strategies in artificial life. 821-822
• 
  Mikiko Sato, Yuji Sato, Mitaro Namiki:
  Acceleration experiment of genetic computations for sudoku solution on multi-core processors. 823-824
• 
  Jong-Hyun Lee, Chang Wook Ahn:
  Improving energy efficiency based on behavioral model in a swarm of cooperative foraging robots. 825-826
• 
  Pedro Sousa, Carla Duarte, Manuel F. M. Barros, Jorge Guilherme, Nuno Horta:
  Optimal OpAmp sizing based on a fuzzy-genetic kernel. 827-828
• 
  Wojciech Jaskowski, Krzysztof Krawiec:
  How many dimensions in co-optimization. 829-830
• 
  Filippo Caschera, Martin M. Hanczyc, Steen Rasmussen:
  Machine learning for drug design, molecular machines and evolvable artificial cells. 831-832
• 
  Todor Dimitrov, Michael Baumann:
  Genetic algorithm with genetic engineering technology for multi-objective dynamic job shop scheduling problems. 833-834
• 
  David Iclanzan, Péter István Fülöp, Camelia Chira, Anca Gog:
  Towards the efficient evolution of particle-based computation in cellular automata. 835-836
• 
  Daniel Leal Souza, Glauber Duarte Monteiro, Tiago Carvalho Martins, Victor Alexandrovich Dmitriev, Otávio Noura Teixeira:
  PSO-GPU: accelerating particle swarm optimization in CUDA-based graphics processing units. 837-838

Introductory tutorials

• 
  Erik D. Goodman:
  Introduction to genetic algorithms. 839-860
• 
  Una-May O'Reilly:
  Genetic programming: a tutorial introduction. 861-874
• 
  Thomas Bäck:
  Evolution strategies: basic introduction. 875-898
• 
  Kenneth A. De Jong:
  Evolutionary computation: a unified approach. 899-912
• 
  Martin Pelikan:
  Probabilistic model-building genetic algorithms. 913-940
• 
  Martin V. Butz:
  Learning classifier systems. 941-962
• 
  Christian Blum:
  Ant colony optimization. 963-990
• 
  Nikolaus Hansen, Anne Auger:
  CMA-ES: evolution strategies and covariance matrix adaptation. 991-1010
• 
  Risto Miikkulainen:
  Evolving neural networks. 1011-1028

Advanced tutorials

• 
  Jonathan E. Rowe:
  Genetic algorithm theory. 1029-1052
• 
  Thomas Jansen, Frank Neumann:
  Computational complexity and evolutionary computation. 1053-1080
• 
  Lee Spector:
  Evolving quantum computer algorithms. 1081-1110
• 
  Dimo Brockhoff:
  Evolutionary multiobjective optimization. 1111-1136
• 
  Carlos Artemio Coello Coello:
  Constraint-handling techniques used with evolutionary algorithms. 1137-1160
• 
  Natalio Krasnogor:
  (Computational) synthetic biology. 1161-1190
• 
  Franz Rothlauf:
  Representations for evolutionary algorithms. 1191-1212
• 
  Tobias Friedrich, Frank Neumann:
  Foundations of evolutionary multi-objective optimization. 1213-1232

Specialized techniques and applications

• 
  Carsten Witt:
  Theory of randomized search heuristics in combinatorial optimization. 1233-1260
• 
  Julian F. Miller, Simon L. Harding:
  GECCO 2011 tutorial: cartesian genetic programming. 1261-1284
• 
  Jaume Bacardit, Xavier Llorà:
  Large scale data mining using genetics-based machine learning. 1285-1310
• 
  Benjamin Doerr:
  Drift analysis. 1311-1320
• 
  Gabriela Ochoa, Matthew R. Hyde, Edmund K. Burke:
  Automated heuristic design. 1321-1342
• 
  Lukás Sekanina:
  Evolution of digital circuits. 1343-1360
• 
  Thomas Bartz-Beielstein, Mike Preuss:
  Automatic and interactive tuning of algorithms. 1361-1380
• 
  Dirk Sudholt:
  Theory of swarm intelligence. 1381-1410
• 
  Stefan Wagner, Gabriel Kronberger:
  Algorithm and experiment design with heuristiclab: an open source optimization environment for research and education. 1411-1438
• 
  Alberto Moraglio:
  Geometry of evolutionary algorithms. 1439-1468
• 
  Marco Tomassini:
  Evolutionary games: the Darwin connection. 1469-1480
• 
  Sara Silva:
  Handling bloat in GP. 1481-1508