GECCO 2010: Portland, Oregon, USA

ACO/Swarm Intelligence Papers

• You Zhou, Ying Tan:
  Particle swarm optimization with triggered mutation and its implementation based on GPU. 1-8
  
• Ziyu Chen, Zhongshi He, Cheng Zhang:
  Particle swarm optimizer with self-adjusting neighborhoods. 9-14
  
• Leonardo Vanneschi, Daniele Codecasa, Giancarlo Mauri:
  An empirical comparison of parallel and distributed particle swarm optimization methods. 15-22
  
• Ying Lin, Xiaomin Hu, Jun Zhang:
  An ant-colony-system-based activity scheduling method for the lifetime maximization of heterogeneous wireless sensor networks. 23-30
  
• Wei-jie Yu, Jun Zhang:
  Pheromone-distribution-based adaptive ant colony system. 31-38
  
• Zhi-hui Zhan, Jun Zhang:
  Self-adaptive differential evolution based on PSO learning strategy. 39-46
  
• Nyree Lemmens, Karl Tuyls:
  Stigmergic landmark routing: a routing algorithm for wireless mobile ad-hoc networks. 47-54
  
• Kalyanmoy Deb, Nikhil Padhye:
  Development of efficient particle swarm optimizers by using concepts from evolutionary algorithms. 55-62
  
• Frank Neumann, Dirk Sudholt, Carsten Witt:
  A few ants are enough: ACO with iteration-best update. 63-70
  
• Manuel López-Ibáñez, Thomas Stützle:
  The impact of design choices of multiobjective antcolony optimization algorithms on performance: an experimental study on the biobjective TSP. 71-78
  

ACO/swarm intelligence posters

• Sarah Salim, Mohsin Javed, Ali Hammad Akbar:
  Honey-bee dancing-inspired architecture for fault tolerance in wireless sensor networks. 79-80
  
• Zhi-hui Zhan, Jun Zhang:
  An parallel particle swarm optimization approach for multiobjective optimization problems. 81-82
  
• Ammar W. Mohemmed, Mengjie Zhang, Will N. Browne:
  Particle swarm optimisation for outlier detection. 83-84
  
• Jeremy B. Brown, Manfred Huber:
  Pseudo-hierarchical ant-based clustering using a heterogeneous agent hierarchy and automatic boundary formation. 85-86
  

Artificial life/robotics/evolvable hardware papers

• Frederick Ducatelle, Gianni A. Di Caro, Luca Maria Gambardella:
  Cooperative self-organization in a heterogeneous swarm robotic system. 87-94
  
• Marcin L. Pilat, Christian Jacob:
  Evolution of vision capabilities in embodied virtual creatures. 95-102
  
• Joel Lehman, Kenneth O. Stanley:
  Revising the evolutionary computation abstraction: minimal criteria novelty search. 103-110
  
• Josh C. Bongard, Gregory S. Hornby:
  Guarding against premature convergence while accelerating evolutionary search. 111-118
  
• Sylvain Koos, Jean-Baptiste Mouret, Stéphane Doncieux:
  Crossing the reality gap in evolutionary robotics by promoting transferable controllers. 119-126
  
• Matt Knudson, Kagan Tumer:
  Coevolution of heterogeneous multi-robot teams. 127-134
  
• Heather Goldsby, David B. Knoester, Charles Ofria:
  Evolution of division of labor in genetically homogenous groups. 135-142
  
• Brian D. Connelly, Benjamin E. Beckmann, Philip K. McKinley:
  Resource abundance promotes the evolution of public goods cooperation. 143-150
  

Artificial life/robotics/evolvable hardware posters

• Jonathan D. Hiller, Hod Lipson:
  Morphological evolution of freeform robots. 151-152
  
• Chrisantha Fernando:
  Neuronal replicators solve the stability-plasticity dilemma. 153-154
  

Bioinformatics, computational, systems and synthetic biology papers

• Ka-Chun Wong, Kwong-Sak Leung, Man Hon Wong:
  Protein structure prediction on a lattice model via multimodal optimization techniques. 155-162
  
• Antonella Farinaccio, Leonardo Vanneschi, Mario Giacobini, Giancarlo Mauri, Paolo Provero:
  On the use of genetic programming for the prediction of survival in cancer. 163-170
  
• Leung-Yau Lo, Tak-Ming Chan, Kin-Hong Lee, Kwong-Sak Leung:
  Challenges rising from learning motif evaluation functions using genetic programming. 171-178
  
• Uday Kamath, Kenneth A. De Jong, Amarda Shehu:
  Selecting predictive features for recognition of hypersensitive sites of regulatory genomic sequences with an evolutionary algorithm. 179-186
  
• Carlos García-Martínez, Claudio Lima, Jamie Twycross, Natalio Krasnogor, Manuel Lozano:
  P system model optimisation by means of evolutionary based search algorithms. 187-194
  
• Ryan J. Urbanowicz, Jason H. Moore:
  The application of michigan-style learning classifiersystems to address genetic heterogeneity and epistasisin association studies. 195-202
  
• Emily Rose Holzinger, Carrie C. Buchanan, Scott M. Dudek, Eric Torstenson, Stephen D. Turner, Marylyn D. Ritchie:
  Initialization parameter sweep in ATHENA: optimizing neural networks for detecting gene-gene interactions in the presence of small main effects. 203-210
  

Bioinformatics, computational, systems and synthetic biology posters

• Emrah Atilgan, Jianjun Hu:
  Efficient protein-ligand docking using sustainable evolutionary algorithm. 211-212
  
• Jirí Kubalík, Petr Buryan, Libor Wagner:
  Solving the DNA fragment assembly problem efficiently using iterative optimization with evolved hypermutations. 213-214
  
• Nicholas A. Sinnott-Armstrong, Casey S. Greene, Jason H. Moore:
  Fast genome-wide epistasis analysis using ant colony optimization for multifactor dimensionality reduction analysis on graphics processing units. 215-216
  

Combinatorial optimization and metaheuristics papers

• He Jiang, Yudong Chen:
  An efficient algorithm for generalized minimum spanning tree problem. 217-224
  
• Serban Iordache:
  Consultant-guided search: a new metaheuristic for combinatorial optimization problems. 225-232
  
• Shelly Xiaonan Wu, Wolfgang Banzhaf:
  A hierarchical cooperative evolutionary algorithm. 233-240
  
• Jacques Bibai, Pierre Savéant, Marc Schoenauer, Vincent Vidal:
  On the generality of parameter tuning in evolutionary planning. 241-248
  
• Jirí Kubalík:
  Efficient stochastic local search algorithm for solving the shortest common supersequence problem. 249-256
  
• Torsten Hildebrandt, Jens Heger, Bernd Scholz-Reiter:
  Towards improved dispatching rules for complex shop floor scenarios: a genetic programming approach. 257-264
  
• K. M. Leung, Xi Zhang:
  Discrete versus continuous parametrization of bank credit rating systems optimization using differential evolution. 265-272
  
• Forrest Stonedahl, Susa H. Stonedahl:
  Heuristics for sampling repetitions in noisy landscapes with fitness caching. 273-280
  
• Zhigang Ren, Zuren Feng:
  An ant colony optimization approach to the multiple-choice multidimensional knapsack problem. 281-288
  

Combinatorial optimization and metaheuristics posters

• Erkan Dogan, Ferhat Erdal, Mehmet Polat Saka:
  Optimum design of grillage systems under code provisions using particle swarm optimization. 289-290
  
• Juan Julián Merelo Guervós, Antonio Miguel Mora, Thomas Philip Runarsson:
  Beating exhaustive search at its own game: revisiting evolutionary mastermind. 291-292
  
• Chun-Wei Tsai, Shih-Pang Tseng, Ming-Chao Chiang, Chu-Sing Yang:
  A framework for accelerating metaheuristics via pattern reduction. 293-294
  
• Steven O. Kimbrough, Ann Kuo, Hoong Chuin Lau:
  Effective heuristic methods for finding non-optimal solutions of interest in constrained optimization models. 295-296
  
• Eunice López-Camacho, Hugo Terashima-Marín, Peter Ross, Manuel Valenzuela-Rendón:
  Problem-state representations in a hyper-heuristic approach for the 2D irregular BPP. 297-298
  
• Elizabeth Montero, María-Cristina Riff, Bertrand Neveu:
  An evaluation of off-line calibration techniques for evolutionary algorithms. 299-300
  
• Wolfgang Steitz, Franz Rothlauf:
  Solving OCST problems with problem-specific guided local search. 301-302
  

Estimation of distribution algorithms (papers)

• Elizabeth Radetic, Martin Pelikan:
  Spurious dependencies and EDA scalability. 303-310
  
• Chung-Yao Chuang, Wen-Lian Hsu:
  Multivariate multi-model approach for globally multimodal problems. 311-318
  
• Jinghui Zhong, Jun Zhang:
  A robust estimation of distribution algorithm for power electronic circuits design. 319-326
  
• Jiadong Yang, Hua Xu, Yunpeng Cai, Peifa Jia:
  Effective structure learning for EDA via L1-regularizedbayesian networks. 327-334
  
• Hoang N. Luong, Hai T. T. Nguyen, Chang Wook Ahn:
  Entropy-based substructural local search for the bayesian optimization algorithm. 335-342
  
• Hai T. T. Nguyen, Hoang N. Luong, Chang Wook Ahn:
  Entropy measurement-based estimation model for bayesian optimization algorithm. 343-350
  
• Peter A. N. Bosman:
  The anticipated mean shift and cluster registration in mixture-based EDAs for multi-objective optimization. 351-358
  
• Rogelio Salinas-Gutiérrez, Arturo Hernández Aguirre, Enrique Raúl Villa Diharce:
  D-vine EDA: a new estimation of distribution algorithm based on regular vines. 359-366
  

Estimation of distribution algorithms poster

• Amin Nikanjam, Hadi Sharifi, B. Hoda Helmi, Adel Torkaman Rahmani:
  A new DSM clustering algorithm for linkage groups identification. 367-368
  

Evolution strategies and evolutionary programming papers

• Alexander Melkozerov, Hans-Georg Beyer:
  On the analysis of self-adaptive evolution strategies on elliptic model: first results. 369-376
  
• Andreas M. Chwatal, Günther R. Raidl, Michael Zöch:
  Fitting multi-planet transit models to photometric time-data series by evolution strategies. 377-384
  
• Dirk V. Arnold, Nikolaus Hansen:
  Active covariance matrix adaptation for the (1+1)-CMA-ES. 385-392
  
• Tobias Glasmachers, Tom Schaul, Yi Sun, Daan Wierstra, Jürgen Schmidhuber:
  Exponential natural evolution strategies. 393-400
  
• Mike Preuss, Günter Rudolph, Simon Wessing:
  Tuning optimization algorithms for real-world problems by means of surrogate modeling. 401-408
  
• Wenyin Gong, Álvaro Fialho, Zhihua Cai:
  Adaptive strategy selection in differential evolution. 409-416
  

Evolution strategies and evolutionary programming posters

• Haiping Ma, Dan Simon:
  Biogeography-based optimization with blended migration for constrained optimization problems. 417-418
  
• Eloy Gonzales, Shingo Mabu, Karla Taboada, Kotaro Hirasawa, Kaoru Shimada:
  Pruning association rules using statistics and genetic relation algoritm. 419-420
  
• Ofer M. Shir, Jonathan Roslund, Herschel Rabitz:
  Forced optimal covariance adaptive learning: modified CMA-ES for efficient hessian determination. 421-422
  

Evolutionary multiobjective optimization papers

• Ruochen Liu, Wei Zhang, Licheng Jiao, Fang Liu, Jingjing Ma:
  A sphere-dominance based preference immune-inspired algorithm for dynamic multi-objective optimization. 423-430
  
• Darrell F. Lochtefeld, Frank W. Ciarallo:
  Deterministic helper-objective sequences applied to job-shop scheduling. 431-438
  
• Jacob Schrum, Risto Miikkulainen:
  Evolving agent behavior in multiobjective domains using fitness-based shaping. 439-446
  
• Kalyanmoy Deb, Amit Saha:
  Finding multiple solutions for multimodal optimization problems using a multi-objective evolutionary approach. 447-454
  
• Tamara Ulrich, Johannes Bader, Eckart Zitzler:
  Integrating decision space diversity into hypervolume-based multiobjective search. 455-462
  
• Miqing Li, Jinhua Zheng, Ruimin Shen, Ke Li, Qizhao Yuan:
  A grid-based fitness strategy for evolutionary many-objective optimization. 463-470
  
• Ilya Loshchilov, Marc Schoenauer, Michèle Sebag:
  A mono surrogate for multiobjective optimization. 471-478
  
• Deepak Sharma, Pierre Collet:
  An archived-based stochastic ranking evolutionary algorithm (asrea) for multi-objective optimization. 479-486
  
• Thomas Voß, Nikolaus Hansen, Christian Igel:
  Improved step size adaptation for the MO-CMA-ES. 487-494
  
• Rudolf Berghammer, Tobias Friedrich, Frank Neumann:
  Set-based multi-objective optimization, indicators, and deteriorative cycles. 495-502
  
• Oliver Kramer, Holger Danielsiek:
  DBSCAN-based multi-objective niching to approximate equivalent pareto-subsets. 503-510
  
• Karl Bringmann, Tobias Friedrich:
  The maximum hypervolume set yields near-optimal approximation. 511-518
  
• Hisao Ishibuchi, Yuji Sakane, Noritaka Tsukamoto, Yusuke Nojima:
  Simultaneous use of different scalarizing functions in MOEA/D. 519-526
  
• Hisao Ishibuchi, Noritaka Tsukamoto, Yuji Sakane, Yusuke Nojima:
  Indicator-based evolutionary algorithm with hypervolume approximation by achievement scalarizing functions. 527-534
  

Evolutionary multiobjective optimization posters

• Francesco Folino, Clara Pizzuti:
  Multiobjective evolutionary community detection for dynamic networks. 535-536
  
• Saúl Zapotecas Martínez, Carlos A. Coello Coello:
  A multi-objective meta-model assisted memetic algorithm with non gradient-based local search. 537-538
  
• D. Dumitrescu, Rodica Ioana Lung, Réka Nagy, Daniela Zaharie, Attila Bartha:
  Exploring evolutionary detected fuzzy equilibria: a link between normative theory and real life. 539-540
  
• Anke K. Hutzschenreuter, Peter A. N. Bosman, Han La Poutré:
  Enhanced hospital resource management using anticipatory policies in online dynamic multi-objective optimization. 541-542
  
• Michael D. Schmidt, Hod Lipson:
  Age-fitness pareto optimization. 543-544
  
• Luis Martí, Jesús García, Antonio Berlanga, José M. Molina:
  Moving away from error-based learning in multi-objective estimation of distribution algorithms. 545-546
  

Generative and developmental systems papers

• Phillip Verbancsics, Kenneth O. Stanley:
  Transfer learning through indirect encoding. 547-554
  
• Keith L. Downing:
  The baldwin effect in developing neural networks. 555-562
  
• Sebastian Risi, Joel Lehman, Kenneth O. Stanley:
  Evolving the placement and density of neurons in the hyperneat substrate. 563-570
  
• Till Steiner, Yaochu Jin, Bernhard Sendhoff:
  Evolving heterochrony for cellular differentiation using vector field embryogeny. 571-578
  
• Simon Harding, Julian F. Miller, Wolfgang Banzhaf:
  Self modifying cartesian genetic programming: finding algorithms that calculate pi and e to arbitrary precision. 579-586
  
• Jean-Baptiste Mouret, Stéphane Doncieux, Benoît Girard:
  Importing the computational neuroscience toolbox into neuro-evolution-application to basal ganglia. 587-594
  
• Martin Trefzer, Tüze Kuyucu, Julian F. Miller, Andy M. Tyrrell:
  Image compression of natural images using artificial gene regulatory networks. 595-602
  
• David B. Knoester, Heather Goldsby, Philip K. McKinley:
  Neuroevolution of mobile ad hoc networks. 603-610
  
• Hirotaka Moriguchi, Shinichi Honiden:
  Sustaining behavioral diversity in NEAT. 611-618
  
• Jan Koutník, Faustino J. Gomez, Jürgen Schmidhuber:
  Evolving neural networks in compressed weight space. 619-626
  
• Joshua E. Auerbach, Josh C. Bongard:
  Evolving CPPNs to grow three-dimensional physical structures. 627-634
  
• Jeff Clune, Benjamin E. Beckmann, Philip K. McKinley, Charles Ofria:
  Investigating whether hyperNEAT produces modular neural networks. 635-642
  

Generative and developmental systems posters

• Josh C. Bongard:
  Morphological scaffolding: how evolution and development improve robot behavior generation. 643-644
  
• Benjamin Inden, Yaochu Jin, Robert Haschke, Helge Ritter:
  NEATfields: evolution of neural fields. 645-646
  
• Terence Soule, Robert B. Heckendorn:
  A developmental algorithm for multi-agent swarms with scalable hierarchies. 647-648
  

Genetic algorithms papers

• Robert Collier, Mark Wineberg:
  Approaches to multidimensional scaling for adaptive landscape visualization. 649-656
  
• Justin Benjamin, Bryant A. Julstrom:
  Breaking ties with secondary fitness in a genetic algorithm for the bin packing problem. 657-664
  
• Martin Pelikan:
  NK landscapes, problem difficulty, and hybrid evolutionary algorithms. 665-672
  
• Wenjin Chen, Kwok Yip Szeto:
  Complex energy landscape mapping by histogram assisted genetic algorithm. 673-680
  
• Roi Yehoshua, Mireille Avigal, Ron Unger:
  Analysis of the effects of lifetime learning on population fitness using vose model. 681-688
  
• Rupesh Tulshyan, Ramnik Arora, Kalyanmoy Deb, Joydeep Dutta:
  Investigating EA solutions for approximate KKT conditions in smooth problems. 689-696
  
• Ta-Chun Lien, Tian-Li Yu, Ying-Shiuan You:
  Co-evolution of cooperative strategies under egoism. 697-704
  
• Thomas Jansen, Christine Zarges:
  Aging beyond restarts. 705-712
  
• Mark Hauschild, Martin Pelikan:
  Network crossover performance on NK landscapes and deceptive problems. 713-720
  
• Fatemeh Vafaee, György Turán, Peter C. Nelson:
  Optimizing genetic operator rates using a markov chain model of genetic algorithms. 721-728
  
• Yun Wen, Hua Xu, Jiadong Yang:
  A heuristic-based hybrid genetic algorithm for heterogeneous multiprocessor scheduling. 729-736
  
• Prakarn Unachak, Erik D. Goodman:
  Solving multiobjective flexible job-shop scheduling using an adaptive representation. 737-742
  
• Bernadete Maria de Mendonça Neta, Gustavo Henrique Diniz Araújo, Frederico Gadelha Guimarães, Renato Cardoso Mesquita:
  A hybrid genetic algorithm for automatic graph drawing based on the topology-shape-metric approach. 743-750
  
• André da Motta Salles Barreto, Heder S. Bernardino, Helio J. C. Barbosa:
  Probabilistic performance profiles for the experimental evaluation of stochastic algorithms. 751-758
  
• Benjamin Doerr, Daniel Johannsen:
  Edge-based representation beats vertex-based representation in shortest path problems. 759-766
  
• Álvaro Fialho, Marc Schoenauer, Michèle Sebag:
  Toward comparison-based adaptive operator selection. 767-774
  
• Severino F. Galán, Ole J. Mengshoel:
  Generalized crowding for genetic algorithms. 775-782
  
• Phillipa Avery, Sushil J. Louis:
  Coevolving influence maps for spatial team tactics in a RTS game. 783-790
  
• Benjamin P. Carlson, Dean F. Hougen:
  Phenotype feedback genetic algorithm operators for heuristic encoding of snakes within hypercubes. 791-798
  
• John Crofford, Brent E. Eskridge, Dean F. Hougen:
  Applying the triple parameter hypothesis to maintenance scheduling. 799-806
  
• Jason E. Cook, Daniel R. Tauritz:
  An exploration into dynamic population sizing. 807-814
  

Genetic algorithms posters

• Aram Ter-Sarkisov, Stephen R. Marsland, Barbara R. Holland:
  The K-bit-swap: a new genetic algorithm operator. 815-816
  
• Roberto De Prisco, Gianluca Zaccagnino, Rocco Zaccagnino:
  EvoBassComposer: a multi-objective genetic algorithm for 4-voice compositions. 817-818
  
• Farhad Nadi, Ahamad Tajudin Abdul Khader, Mohammed Azmi Al-Betar:
  Adaptive genetic algorithm using harmony search. 819-820
  
• Victor Kureichik, Boris K. Lebedev, Oleg B. Lebedev:
  Hybrid evolutionary algorithm of planning VLSI. 821-822
  
• Matthew A. Addicoat, Zoe E. Brain:
  Using a Meta-GA for parametric optimization of simple gas in the computational chemistry domain. 823-824
  
• Hazem M. Abbas:
  Mixed-coded evolutionary algorithm for Gaussian mixture maximum likelihood clustering with model selection. 825-826
  
• D. Dumitrescu, Rodica Ioana Lung, Noémi Gaskó, Tudor Dan Mihoc:
  Evolutionary detection of aumann equilibrium. 827-828
  
• Anna Isabel Esparcia-Alcázar, Anaís Martínez-García, Antonio Miguel Mora, Juan Julián Merelo Guervós, Pablo García-Sánchez:
  Genetic evolution of fuzzy finite state machines to control bots in a first-person shooter game. 829-830
  
• Patricia Ortegon-Cano, Diego A. Hartasanchez, Christopher R. Stephens:
  Why recombination should be adaptive. 831-832
  
• Timothy Meekhof, Terence Soule:
  Noise pressure: systematic overestimation of population fitness in genetic algorithms with noisy fitness functions. 833-834
  
• Juan Arturo Herrera Ortiz, Carlos Oliver-Morales, Katya Rodríguez-Vázquez:
  Amount and type of information: a GA-hardness taxonomy. 835-836
  

Genetic programming papers

• Joel Lehman, Kenneth O. Stanley:
  Efficiently evolving programs through the search for novelty. 837-844
  
• Urvesh Bhowan, Mengjie Zhang, Mark Johnston:
  AUC analysis of the pareto-front using multi-objective GP for classification with unbalanced data. 845-852
  
• Peter Lichodzijewski, Malcolm I. Heywood:
  Symbiosis, complexification and simplicity under GP. 853-860
  
• Leonardo Trujillo, Pierrick Legrand, Jacques Lévy Véhel:
  The estimation of hölderian regularity using genetic programming. 861-868
  
• Nguyen Quang Uy, Nguyen Xuan Hoai, Michael O'Neill, Bob McKay:
  Semantics based crossover for boolean problems. 869-876
  
• Leonardo Vanneschi, Mauro Castelli, Sara Silva:
  Measuring bloat, overfitting and functional complexity in genetic programming. 877-884
  
• Carlton Downey, Mengjie Zhang, Will N. Browne:
  New crossover operators in linear genetic programming for multiclass object classification. 885-892
  
• R. Muhammad Atif Azad, Conor Ryan:
  Abstract functions and lifetime learning in genetic programming for symbolic regression. 893-900
  
• Edgar Galván López, James McDermott, Michael O'Neill, Anthony Brabazon:
  Towards an understanding of locality in genetic programming. 901-908
  
• Amelia Zafra, Sebastián Ventura:
  Grammar guided genetic programming for multiple instance learning: an experimental study. 909-916
  
• Cassio Pennachin, Moshe Looks, João A. de Vasconcelos:
  Robust symbolic regression with affine arithmetic. 917-924
  
• Josh C. Bongard:
  A probabilistic functional crossover operator for genetic programming. 925-932
  
• Douglas Adriano Augusto, Helio José Corrêa Barbosa, Nelson Francisco Favilla Ebecken:
  Coevolutionary multi-population genetic programming for data classification. 933-940
  
• Katya Vladislavleva, Kalyan Veeramachaneni, Matt Burland, Jason Parcon, Una-May O'Reilly:
  Knowledge mining with genetic programming methods for variable selection in flavor design. 941-948
  
• Michael D. Schmidt, Hod Lipson:
  Predicting solution rank to improve performance. 949-956
  
• Blair Foster, Anil Somayaji:
  Object-level recombination of commodity applications. 957-964
  
• Ethan Fast, Claire Le Goues, Stephanie Forrest, Westley Weimer:
  Designing better fitness functions for automated program repair. 965-972
  

Genetic programming posters

• Henrique G. Momm, Greg Easson:
  Population restarting: a study case of feature extraction from remotely sensed imagery using textural information. 973-974
  
• David F. Barrero, David Camacho, María D. R-Moreno:
  Confidence intervals of success rates in evolutionary computation. 975-976
  
• Dilip P. Ahalpara:
  Improved forecasting of time series data of real system using genetic programming. 977-978
  
• Jun Wang, Ying Tan:
  A novel genetic programming based morphological image analysis algorithm. 979-980
  
• Dara Curran, Eugene C. Freuder, Thomas Jansen:
  Incremental evolution of local search heuristics. 981-982
  
• Zbysek Gajda, Lukás Sekanina:
  When does Cartesian genetic programming minimize the phenotype size implicitly? 983-984
  
• Cruz E. Borges, César Luis Alonso, José L. Montaña:
  Model selection in genetic programming. 985-986
  
• Michael McMullin, Terence Soule:
  Constant versus variable arity operators in genetic programming. 987-988
  
• Fernando Alonso, Loïc Martínez, Agustín Santamaría, Aurora Pérez-Pérez, Juan Pedro Valente:
  GGGP-based method for modeling time series: operator selection, parameter optimization and expert evaluation. 989-990
  

Genetics based machine learning

• Carlos D. Toledo-Suárez:
  A first assessment of the use of extended relational alphabets in accuracy classifier systems. 991-998
  
• Edward P. Manning:
  Coevolution in a large search space using resource-limited nash memory. 999-1006
  
• Ulf Johansson, Rikard König, Lars Niklasson:
  Genetic rule extraction optimizing brier score. 1007-1014
  
• Clemens Lode, Urban Richter, Hartmut Schmeck:
  Adaption of XCS to multi-learner predator/prey scenarios. 1015-1022
  
• Albert Orriols-Puig, Xavier Llorà, David E. Goldberg:
  How XCS deals with rarities in domains with continuous attributes. 1023-1030
  
• Matthijs Snel, Shimon Whiteson:
  Multi-task evolutionary shaping without pre-specified representations. 1031-1038
  
• María A. Franco, Natalio Krasnogor, Jaume Bacardit:
  Speeding up the evaluation of evolutionary learning systems using GPGPUs. 1039-1046
  
• Maciej Liskiewicz, Johannes Textor:
  Negative selection algorithms without generating detectors. 1047-1054
  
• Núria Macià, Albert Orriols-Puig, Ester Bernadó-Mansilla:
  In search of targeted-complexity problems. 1055-1062
  
• Ruochen Liu, Hejun Ning, Wei Zhang, Licheng Jiao:
  A clonal selection clustering algorithm using pointed symmetry-based distance measure. 1063-1064
  
• Chi Su, Yang Gao, Chun Cao:
  Learning classifier system using both labeled and unlabeled data. 1065-1066
  
• Mohammad Behdad, Tim French, Luigi Barone, Mohammed Bennamoun:
  On the problems of using learning classifier systems for fraud detection. 1067-1068
  
• Aruanda Simões Goncalves Meiguins, Alex Alves Freitas, Roberto Célio Limão de Oliveira, Samuel F. S. Junior, Bianchi Serique Meiguins:
  An estimation of distribution algorithm for the automatic generation of clustering algorithms. 1069-1070
  
• Petr Buryan, Jirí Kubalík:
  Context-sensitive refinements for stochasticoptimization algorithms in inductive logic programming. 1071-1072
  
• Padmini Rajagopalan, Aditya Rawal, Risto Miikkulainen:
  Emergence of competitive and cooperative behavior using coevolution. 1073-1074
  

Parallel evolutionary systems papers

• Maxwell Walton, Gary Gréwal, Gerarda Darlington:
  Parallel FPGA-based implementation of scatter search. 1075-1082
  
• Gabriel Luque, Enrique Alba:
  Selection pressure and takeover time of distributed evolutionary algorithms. 1083-1088
  
• Thé Van Luong, Nouredine Melab, El-Ghazali Talbi:
  GPU-based island model for evolutionary algorithms. 1089-1096
  
• Dana Vrajitoru:
  Shared memory genetic algorithms in a multi-agent context. 1097-1104
  
• Jörg Lässig, Dirk Sudholt:
  The benefit of migration in parallel evolutionary algorithms. 1105-1112
  

Parallel evolutionary systems posters

• Chi Zhou:
  Fast parallelization of differential evolution algorithm using MapReduce. 1113-1114
  

Real world applications papers

• Kaoru Shimada, Kotaro Hirasawa:
  A method of association rule analysis for incomplete database using genetic network programming. 1115-1122
  
• Max Salichon, Kagan Tumer:
  A neuro-evolutionary approach to micro aerial vehicle control. 1123-1130
  
• Jack F. Shepherd III, Kagan Tumer:
  Robust neuro-control for a micro quadrotor. 1131-1138
  
• Garnett Carl Wilson, Wolfgang Banzhaf:
  Interday foreign exchange trading using linear genetic programming. 1139-1146
  
• Leonardo Trujillo, Pierrick Legrand, Gustavo Olague, Cynthia B. Pérez:
  Optimization of the hölder image descriptor using a genetic algorithm. 1147-1154
  
• Christie Myburgh, Kalyanmoy Deb:
  Evolutionary algorithms in large-scale open pit mine scheduling. 1155-1162
  
• Aaron Garrett, Zizhong Chen, Daniel Eric Smith:
  Constructing numerically stable real number codes using evolutionary computation. 1163-1170
  
• Jirí Jaros, Vaclav Dvorak:
  Evolutionary-based conflict-free scheduling of collective communications on spidergon NoCs. 1171-1178
  
• Keehyung Kim, Robert Ian (Bob) McKay, Byung Ro Moon:
  Multiobjective evolutionary algorithms for dynamic social network clustering. 1179-1186
  
• Edgar Reehuis, Thomas Bäck:
  Mixed-integer evolution strategy using multiobjective selection applied to warehouse design optimization. 1187-1194
  
• Forrest Stonedahl, William Rand, Uri Wilensky:
  Evolving viral marketing strategies. 1195-1202
  
• Mohammed Azmi Al-Betar, Ahamad Tajudin Abdul Khader, Farhad Nadi:
  Selection mechanisms in memory consideration for examination timetabling with harmony search. 1203-1210
  
• Keehyung Kim, Byung Ro Moon:
  Malware detection based on dependency graph using hybrid genetic algorithm. 1211-1218
  
• Seung-Kyu Lee, Byung Ro Moon:
  A new modular genetic programming for finding attractive technical patterns in stock markets. 1219-1226
  
• José Manuel Colmenar, José L. Risco-Martín, David Atienza, Oscar Garnica, José Ignacio Hidalgo, Juan Lanchares:
  Improving reliability of embedded systems through dynamic memory manager optimization using grammatical evolution. 1227-1234
  
• Mirela Ovreiu, Dan Simon:
  Biogeography-based optimization of neuro-fuzzy system parameters for diagnosis of cardiac disease. 1235-1242
  
• Giovanni Stracquadanio, Concetta Drago, Vittorio Romano, Giuseppe Nicosia:
  Multi-objective optimization of doping profile in semiconductor design. 1243-1250
  
• Gerulf K. M. Pedersen, Martin V. Butz:
  Evolving robust controller parameters using covariance matrix adaptation. 1251-1258
  
• Nikhil Padhye, Kalyanmoy Deb:
  Evolutionary multi-objective optimization and decision making for selective laser sintering. 1259-1266
  
• Marco Ceriani, Fabrizio Ferrandi, Pier Luca Lanzi, Donatella Sciuto, Antonino Tumeo:
  Multiprocessor systems-on-chip synthesis using multi-objective evolutionary computation. 1267-1274
  
• Makoto Tanji, Hitoshi Iba:
  ConBreO: a music performance rendering system using hybrid approach of IEC and automated evolution. 1275-1282
  
• Steven O. Kimbrough, Ann Kuo:
  On heuristics for two-sided matching: revisiting the stable marriage problem as a multiobjective problem. 1283-1290
  
• Kalyan Veeramachaneni, Katya Vladislavleva, Matt Burland, Jason Parcon, Una-May O'Reilly:
  Evolutionary optimization of flavors. 1291-1298
  
• Elijah Mayfield, Carolyn Penstein Rosé:
  Using feature construction to avoid large feature spaces in text classification. 1299-1306
  

Real world applications posters

• Alejandro Sierra, Vicente Ponsoda:
  Shorter, more reliable and valid tests by means of a genetic algorithm. 1307-1308
  
• Yoon-Seok Choi, Bon-Ki Koo, Byung Ro Moon:
  Optimization of an image set by genetic feature selection for real-time photomosaics. 1309-1310
  
• Toshiharu Sugawara, Kensuke Fukuda, Toshio Hirotsu, Satoshi Kurihara:
  Adaptive probabilistic task allocation in large-scale multi-agent systems and its evaluation. 1311-1312
  
• Lu Yu, Shingo Mabu, Jin Zhou, Shinji Eto, Kotaro Hirasawa:
  A double-deck elevator systems controller with idle cage assignment algorithm using genetic network programming. 1313-1314
  
• Ricardo de A. Araújo, Adriano L. I. de Oliveira, Sérgio C. B. Soares:
  A covariance matrix adaptation based evolutionary methodology for phase adjustment in financial time series forecasting. 1315-1316
  
• David Mosnier, Frédéric Gillot, Antoine Ducloux, Mohamed Ichchou:
  Integrated pre-design step methodology based onmulti-objective evolutionary optimization. 1317-1318
  
• Ying-Shiuan You, Tian-Li Yu, Ta-Chun Lien:
  Psychological preference-based optimization framework on the nurse scheduling problem. 1319-1320
  
• Mikiko Sato, Yuji Sato, Mitaro Namiki:
  Proposal of a multi-core processor architecture for effective evolutionary computation. 1321-1322
  
• Cem Celal Tutum, Jesper Henri Hattel:
  Multi-objective optimization of process parameters in friction stir welding. 1323-1324
  
• Sohini Roychoudhury, Sanjoy Das, Caterina M. Scoglio, Swagatam Das, Bijaya K. Panigrahi, Shyam S. Pattnaik:
  Mitigation strategies in epidemics: evolutionary optimization using a hierarchy of objective functions. 1325-1326
  
• Ralph Evins, Philip Pointer, Ravi Vaidyanathan:
  Configuration of a genetic algorithm for multi-objective optimisation of solar gain to buildings. 1327-1328
  
• Stefano Di Carlo, Ernesto Sánchez, Alberto Scionti, Giovanni Squillero, Alberto Paolo Tonda, Matteo Falasconi:
  Towards drift correction in chemical sensors using an evolutionary strategy. 1329-1330
  
• Muhammad Jamal Afridi, Salman Manzoor, Umer Rasheed, Mariam Ahmed, Faraz Kunwar:
  Performance evaluation of evolutionary algorithms for road detection. 1331-1332
  

Search-based software engineering papers

• He Jiang, Jifeng Xuan, Zhilei Ren:
  Approximate backbone based multilevel algorithm for next release problem. 1333-1340
  
• Adam C. Jensen, Betty H. C. Cheng:
  On the use of genetic programming for automated refactoring and the introduction of design patterns. 1341-1348
  
• Andreas Windisch:
  Search-based test data generation from stateflow statecharts. 1349-1356
  
• Yuanyuan Zhang, Enrique Alba, Juan José Durillo, Sigrid Eldh, Mark Harman:
  Today/future importance analysis. 1357-1364
  
• Zhihong Xu, Myra B. Cohen, Gregg Rothermel:
  Factors affecting the use of genetic algorithms in test suite augmentation. 1365-1372
  
• Alexander P. Conrad, Robert S. Roos, Gregory M. Kapfhammer:
  Empirically studying the role of selection operators duringsearch-based test suite prioritization. 1373-1380
  
• Mathew Hall, Phil McMinn, Neil Walkinshaw:
  Superstate identification for state machines using search-based clustering. 1381-1388
  

Search-based software engineering posters

• Thomas Kremmel, Jirí Kubalík, Stefan Biffl:
  Multiobjective evolutionary algorithm for software project portfolio optimization. 1389-1390
  
• Josh L. Wilkerson, Daniel R. Tauritz:
  Coevolutionary automated software correction. 1391-1392
  

Theory papers

• Timo Kötzing, Per Kristian Lehre, Frank Neumann, Pietro Simone Oliveto:
  Ant colony optimization and the minimum cut problem. 1393-1400
  
• Youhei Akimoto, Yuichi Nagata, Isao Ono, Shigenobu Kobayashi:
  Theoretical analysis of evolutionary computation on continuously differentiable functions. 1401-1408
  
• L. Darrell Whitley, J. Francisco Chicano, Enrique Alba, Francisco Luna:
  Elementary landscapes of frequency assignment problems. 1409-1416
  
• Swagato Sanyal, Raja S, Somenath Biswas:
  Necessary and sufficient conditions for success of the metropolis algorithm for optimization. 1417-1424
  
• J. Francisco Chicano, Gabriel Luque, Enrique Alba:
  Elementary landscape decomposition of the quadratic assignment problem. 1425-1432
  
• Daniel Johannsen, Piyush P. Kurur, Johannes Lengler:
  Can quantum search accelerate evolutionary algorithms? 1433-1440
  
• Per Kristian Lehre, Carsten Witt:
  Black-box search by unbiased variation. 1441-1448
  
• Benjamin Doerr, Daniel Johannsen, Carola Winzen:
  Multiplicative drift analysis. 1449-1456
  
• Benjamin Doerr, Mahmoud Fouz, Carsten Witt:
  Quasirandom evolutionary algorithms. 1457-1464
  
• Christian Horoba, Dirk Sudholt:
  Ant colony optimization for stochastic shortest path problems. 1465-1472
  

Theory posters

• Luca Manzoni, Leonardo Vanneschi, Giancarlo Mauri:
  Definition of a crossover based distance for genetic algorithms. 1473-1474
  
• Andrea Valsecchi, Leonardo Vanneschi, Giancarlo Mauri:
  Optimization speed and fair sets of functions. 1475-1476
  

GECCO 2009 omission (errata)

• Paulo S. G. de Mattos Neto, Aranildo Rodrigues Lima Junior, Tiago A. E. Ferreira:
  Time series forecasting using a perturbative intelligent system. 1477-1478
  

Last update Fri May 25 08:14:37 2012 CET by the DBLP Team — Data released under the ODC-BY 1.0 license — See also our legal information page