Black box optimization benchmarking 2010 (BBOB 2010)

• 
  Thomas Weise, Li Niu, Ke Tang: AOAB: automated optimization algorithm benchmarking. 1479-1486
• 
  Raymond Ros: Comparison of NEWUOA with different numbers of interpolation points on the BBOB noiseless testbed. 1487-1494
• 
  Raymond Ros: Comparison of NEWUOA with different numbers of interpolation points on the BBOB noisy testbed. 1495-1502
• 
  Raymond Ros: Black-box optimization benchmarking the IPOP-CMA-ES on the noiseless testbed: comparison to the BIPOP-CMA-ES. 1503-1510
• 
  Raymond Ros: Black-box optimization benchmarking the IPOP-CMA-ES on the noisy testbed: comparison to the BIPOP-CMA-ES. 1511-1518
• 
  Nikolaus Hansen, Raymond Ros: Black-box optimization benchmarking of NEWUOA compared to BIPOP-CMA-ES: on the BBOB noiseless testbed. 1519-1526
• 
  Álvaro Fialho, Wenyin Gong, Zhihua Cai: Probability matching-based adaptive strategy selection vs. uniform strategy selection within differential evolution: an empirical comparison on the bbob-2010 noiseless testbed. 1527-1534
• 
  Álvaro Fialho, Marc Schoenauer, Michèle Sebag: Fitness-AUC bandit adaptive strategy selection vs. the probability matching one within differential evolution: an empirical comparison on the bbob-2010 noiseless testbed. 1535-1542
• 
  Anne Auger, Dimo Brockhoff, Nikolaus Hansen: Comparing the (1+1)-CMA-ES with a mirrored (1+2)-CMA-ES with sequential selection on the noiseless BBOB-2010 testbed. 1543-1550
• 
  Anne Auger, Dimo Brockhoff, Nikolaus Hansen: Mirrored variants of the (1, 2)-CMA-ES compared on the noiseless BBOB-2010 testbed. 1551-1558
• 
  Anne Auger, Dimo Brockhoff, Nikolaus Hansen: Mirrored variants of the (1, 4)-CMA-ES compared on the noiseless BBOB-2010 testbed. 1559-1566
• 
  Jirí Kubalík: Black-box optimization benchmarking of two variants of the POEMS algorithm on the noiseless testbed. 1567-1574
• 
  Anne Auger, Dimo Brockhoff, Nikolaus Hansen: Mirrored variants of the (1, 2)-CMA-ES compared on the noisy BBOB-2010 testbed. 1575-1582
• 
  Anne Auger, Dimo Brockhoff, Nikolaus Hansen: Mirrored variants of the (1, 4)-CMA-ES compared on the noisy BBOB-2010 testbed. 1583-1590
• 
  Anne Auger, Dimo Brockhoff, Nikolaus Hansen: Investigating the impact of sequential selection in the (1, 2)-CMA-ES on the noiseless BBOB-2010 testbed. 1591-1596
• 
  Anne Auger, Dimo Brockhoff, Nikolaus Hansen: Investigating the impact of sequential selection in the (1, 4)-CMA-ES on the noiseless BBOB-2010 testbed. 1597-1604
• 
  Anne Auger, Dimo Brockhoff, Nikolaus Hansen: Investigating the impact of sequential selection in the (1, 2)-CMA-ES on the noisy BBOB-2010 testbed. 1605-1610
• 
  Anne Auger, Dimo Brockhoff, Nikolaus Hansen: Investigating the impact of sequential selection in the (1, 4)-CMA-ES on the noisy BBOB-2010 testbed. 1611-1616
• 
  Anne Auger, Dimo Brockhoff, Nikolaus Hansen: Benchmarking the (1, 4)-CMA-ES with mirrored sampling and sequential selection on the noiseless BBOB-2010 testbed. 1617-1624
• 
  Anne Auger, Dimo Brockhoff, Nikolaus Hansen: Benchmarking the (1, 4)-CMA-ES with mirrored sampling and sequential selection on the noisy BBOB-2010 testbed. 1625-1632
• 
  Steffen Finck, Hans-Georg Beyer: Benchmarking CMA-EGS on the BBOB 2010 noiseless function testbed. 1633-1640
• 
  Steffen Finck, Hans-Georg Beyer: Benchmarking CMA-EGS on the BBOB 2010 noisy function testbed. 1641-1648
• 
  Antonio LaTorre, Santiago Muelas, José María Peña: Benchmarking a MOS-based algorithm on the BBOB-2010 noiseless function testbed. 1649-1656
• 
  Steffen Finck, Hans-Georg Beyer: Benchmarking SPSA on BBOB-2010 noiseless function testbed. 1657-1664
• 
  Steffen Finck, Hans-Georg Beyer: Benchmarking SPSA on BBOB-2010 noisy function testbed. 1665-1672
• 
  Nikolaus Hansen, Raymond Ros: Benchmarking a weighted negative covariance matrix update on the BBOB-2010 noiseless testbed. 1673-1680
• 
  Nikolaus Hansen, Raymond Ros: Benchmarking a weighted negative covariance matrix update on the BBOB-2010 noisy testbed. 1681-1688
• 
  Nikolaus Hansen, Anne Auger, Raymond Ros, Steffen Finck, Petr Posík: Comparing results of 31 algorithms from the black-box optimization benchmarking BBOB-2009. 1689-1696
• 
  Petr Posík: Comparison of cauchy EDA and BIPOP-CMA-ES algorithms on the BBOB noiseless testbed. 1697-1702
• 
  Petr Posík, Jirí Kubalík: Comparison of cauchy EDA and pPOEMS algorithms on the BBOB noiseless testbed. 1703-1710
• 
  Mike Preuss: Niching the CMA-ES via nearest-better clustering. 1711-1718
• 
  Mohammed El-Abd: Black-box optimization benchmarking for noiseless function testbed using artificial bee colony algorithm. 1719-1724
• 
  Antonio LaTorre, Santiago Muelas, José María Peña: Benchmarking a MOS-based algorithm on the BBOB-2010 noisy function testbed. 1725-1730
• 
  Thanh-Do Tran, Gang-Gyoo Jin: Real-coded genetic algorithm benchmarked on noiseless black-box optimization testbed. 1731-1738
• 
  Thanh-Do Tran, Gang-Gyoo Jin: Benchmarking real-coded genetic algorithm on noisy black-box optimization testbed. 1739-1744
• 
  Petr Posík: Comparison of cauchy EDA and rosenbrock's algorithms on the BBOB noiseless testbed. 1745-1752
• 
  Petr Posík: Comparison of cauchy EDA and G3PCX algorithms on the BBOB noiseless testbed. 1753-1760
• 
  Petr Posík: Comparison of G3PCX and Rosenbrock's algorithms on the BBOB noiseless testbed. 1761-1768

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

• 
  Terence Soule, Robert B. Heckendorn: A developmental approach to evolving scalable hierarchies for multi-agent swarms. 1769-1776
• 
  Rhonda Hoenigman, Elizabeth Bradley, Nichole Barger: AgentScapes: designing water efficient landscapes using distributed agent-based optimization. 1777-1784
• 
  Justin T. H. Smith: Implicit fitness and heterogeneous preferences in the genetic algorithm. 1785-1792
• 
  Kan-Leung Cheng, Inon Zuckerman, Ugur Kuter, Dana S. Nau: Emergence of cooperative societies in evolutionary games. 1793-1800
• 
  Chao Yang, Setsuya Kurahashi, Isao Ono, Takao Terano: Pattern-oriented inverse simulation for agent-based modeling: an analysis of family strategies. 1801-1808
• 
  Emily M. Zechman: Integrating complex adaptive system simulation and evolutionary computation to support water infrastructure threat management. 1809-1816

Evolutionary computation techniques for constraint handling

• 
  Amy FitzGerald, Diarmuid P. O'Donoghue: Biologically inspired non-mendelian repair for constraint handling in evolutionary algorithms. 1817-1824
• 
  Madalina Raschip, Henri Luchian: Using messy genetic algorithms for solving the winner determination problem. 1825-1832
• 
  Steven O. Kimbrough, Ann Kuo, Hoong Chuin Lau: On decision support for deliberating with constraints in constrained optimization models. 1833-1840

Entropy, information and complexity

• 
  Russ Abbott: From energy to information and back. 1841-1842
• 
  John Milton, Paul J. Kennedy: Entropy profiles of ranked and random populations. 1843-1850
• 
  Stuart W. Card: Information distance based fitness and diversity metrics. 1851-1854

Thirteenth international workshop on learning classifier systems

• 
  María A. Franco, Natalio Krasnogor, Jaume Bacardit: Analysing bioHEL using challenging boolean functions. 1855-1862
• 
  Patrick O. Stalph, Jérémie Rubinsztajn, Olivier Sigaud, Martin V. Butz: A comparative study: function approximation with LWPR and XCSF. 1863-1870
• 
  Anthony Knittel: An activation reinforcement based classifier system for balancing generalisation and specialisation (ARCS). 1871-1878
• 
  Gilles Énée, Mathias Péroumalnaïk: Speedup character-based matching in learning classifier systems with Xor. 1879-1884
• 
  Karthik Kuber, Chilukuri K. Mohan: Information theoretic fitness measures for learning classifier systems. 1885-1892
• 
  Mohammad Behdad, Luigi Barone, Tim French, Mohammed Bennamoun: An investigation of real-valued accuracy-based learning classifier systems for electronic fraud detection. 1893-1900
• 
  Mathias Péroumalnaïk, Gilles Énée: Prediction using Pittsburgh learning classifier systems: APCS use case. 1901-1908

Medical applications of genetic and evolutionary computation (MedGEC)

• 
  Muhammad Arsalan, Sana Ambreen Malik, Asifullah Khan: Intelligent threshold selection for reversible watermarking of medical images. 1909-1914
• 
  Stephan M. Winkler, Michael Affenzeller, Witold Jacak, Herbert Stekel: Classification of tumor marker values using heuristic data mining methods. 1915-1922
• 
  Julian F. Miller, Stephen L. Smith, Yuan Zhang: Detection of microcalcifications in mammograms using multi-chromosome Cartesian genetic programming. 1923-1930
• 
  Robert M. Patton, Barbara G. Beckerman, Thomas E. Potok, Jim N. Treadwell: Genetic algorithm for analysis of abdominal aortic aneurysms in radiology reports. 1931-1936

Optimization by building and using probabilistic models (OBUPM-2010)

• 
  Petr Posik: Stochastic local search in continuous domains: questions to be answered when designing a novel algorithm. 1937-1944
• 
  Fernando G. Lobo, Cláudio F. Lima: Towards automated selection of estimation of distribution algorithms. 1945-1952
• 
  Dirk Thierens: Linkage tree genetic algorithm: first results. 1953-1958

Theoretical aspects of evolutionary multiobjective optimization - current status and future trends

• 
  Manuel López-Ibáñez, Thomas Stützle, Luis Paquete: Graphical tools for the analysis of bi-objective optimization algorithms: [workshop on theoretical aspects of evolutionary multiobjective optimization]. 1959-1962
• 
  Michael Emmerich, André H. Deutz, Rui Li, Johannes W. Kruisselbrink: Getting lost or getting trapped: on the effect of moves toincomparable points in multiobjective hillclimbing. 1963-1966
• 
  Adriana Lara, Oliver Schütze, Carlos A. Coello Coello: New challenges for memetic algorithms on continuous multi-objective problems. 1967-1970
• 
  Oliver Schütze, Xavier Esquivel, Adriana Lara, Carlos A. Coello Coello: Some comments on GD and IGD and relations to the Hausdorff distance. 1971-1974
• 
  Thomas Voß, Tobias Friedrich, Karl Bringmann, Christian Igel: Scaling up indicator-based MOEAs by approximating the least hypervolume contributor: a preliminary study. 1975-1978
• 
  Ilya Loshchilov, Marc Schoenauer, Michèle Sebag: A pareto-compliant surrogate approach for multiobjective optimization. 1979-1982

Symbolic regression workshop

• 
  Randall K. McRee: Symbolic regression using nearest neighbor indexing. 1983-1990
• 
  Pawel Widera, Jaume Bacardit, Natalio Krasnogor, Carlos García-Martínez, Manuel Lozano: Evolutionary symbolic discovery for bioinformatics, systems and synthetic biology. 1991-1998

Graduate student workshop

• 
  Felix Dobslaw: An experimental study on robust parameter settings. 1999-2002
• 
  Ralph Evins: Configuration of a genetic algorithm for multi-objective optimisation of solar gain to buildings. 2003-2006
• 
  Jae-Woo Kim: Evolutionary learning in networked multi-agent organizations. 2007-2010
• 
  Adriana Lara, Carlos A. Coello Coello, Oliver Schütze: Using gradient information for multi-objective problems in the evolutionary context. 2011-2014
• 
  Aranildo Rodrigues Lima Junior, David Augusto Silva, Paulo Salgado Mattos Neto, Tiago A. E. Ferreira: An experimental study of fitness function and time series forecasting using artificial neural networks. 2015-2018
• 
  Affiani Machmudah, Setyamartana Parman, Azman Zainuddin: UAV bezier curve maneuver planning using genetic algorithm. 2019-2022
• 
  Raja Muhammad Asif Zahoor, Junaid Ali Khan, Ijaz Mansoor Qureshi: Heuristic computational approach using swarm intelligence in solving fractional differential equations. 2023-2026
• 
  Thanh-Do Tran, Gang-Gyoo Jin: Evolving solutions in evolutionary optimization based on a dynamic system model. 2027-2030
• 
  Saúl Zapotecas Martínez, Carlos A. Coello Coello: A novel diversification strategy for multi-objective evolutionary algorithms. 2031-2034
• 
  Zack Z. Zhu: Constraint handling with modified hypervolume indicator for multi-objective optimization problems. 2035-2038

Undergraduate student workshop

• 
  Shawn Aldridge, Michael R. Peterson, Britny Herzog: Image sets for the training of image processing systems. 2039-2042
• 
  Brendan J. Babb: Can evolved forward transforms do better than wavelets. 2043-2046
• 
  John M. Crofford: Is the triple parameter hypothesis generalizable. 2047-2050
• 
  Harikrishna Narasimhan, Sanjeev Satheesh, Dinesh Sriram: Automatic summarization of cricket video events using genetic algorithm. 2051-2054
• 
  Oleg Parinov: The implementation and improvements of genetic algorithm for job-shop scheduling problems. 2055-2058

Late breaking abstracts

• 
  Adrian K. Agogino: Component evolution for large scale air traffic optimization. 2059-2060
• 
  Eun Yeong Ahn, Tracy Mullen, John Yen: Finding feature transformation functions using genetic algorithm. 2061-2062
• 
  Yoseph Tafesse Azene, Rajkumar Roy: Multi-stage, multi-objective process optimisation. 2063-2064
• 
  André Ferry Barreira, Carlos Eduardo de Jesus Guimarães Oliveira, Otávio Noura Teixeira, Roberto Célio Limão de Oliveira: Evolutionary artificial immune system optimization. 2065-2066
• 
  Kan-Leung Cheng, Inon Zuckerman, Ugur Kuter, Dana S. Nau: Emergence of cooperative societies in evolutionary games. 2067-2068
• 
  Omid David-Tabibi, Nathan S. Netanyahu, Yoav Rosenberg, Moshe Shimoni: Genetic algorithms for automatic classification of moving objects. 2069-2070
• 
  Oliver Flasch, Olaf Mersmann, Thomas Bartz-Beielstein: RGP: an open source genetic programming system for the R environment. 2071-2072
• 
  Sayan Ghosh, Swagatam Das, Sanjoy Das: On the asymptotic convergence of differential evolution in continuous spaces: a control theoretic approach. 2073-2074
• 
  Arnob Ghosh, Aritra Chowdhury, Ritwik Giri, Swagatam Das, Sanjoy Das: A fitness-based adaptation scheme for control parameters in differential evolution. 2075-2076
• 
  Kyle Ira Harrington, Jordan B. Pollack: Robot phylogenetics. 2077-2078
• 
  Manar I. Hosny, Christine L. Mumford: An adaptive hybrid VNS/SA approach to the one-commodity pickup and delivery problem. 2079-2080
• 
  Haigen Hu, Lihong Xu, Erik D. Goodman: A control optimization algorithm for greenhouse climate control problems. 2081-2082
• 
  John Hurley: LESR CLASS: an LCS for securities trading rulesets. 2083-2084
• 
  Ilknur Icke, Andrew Rosenberg: Dimensionality reduction using symbolic regression. 2085-2086
• 
  Serban Iordache: Consultant-guided search combined with local search for the traveling salesman problem. 2087-2088
• 
  Serban Iordache: Consultant-guided search algorithms for the quadratic assignment problem. 2089-2090
• 
  Steven Orla Kimbrough, David Harlan Wood: Randomized interpolation: a crossover operator producing children at a constraint transition. 2091-2092
• 
  Sisir Koppaka, Ashish Ranjan Hota: Superior exploration-exploitation balance with quantum-inspired hadamard walks. 2093-2094
• 
  James Kukunas, Robert D. Cupper, Gregory M. Kapfhammer: A genetic algorithm to improve linux kernel performance on resource-constrained devices. 2095-2096
• 
  Rui Li, Michel R. V. Chaudron, René C. Ladan: Towards automated software architectures design using model transformations and evolutionary algorithms. 2097-2098
• 
  Mitsukuni Matayoshi: Corner junction: a new strategy for 2d strip packing. 2099-2100
• 
  Ryan J. Meuth: Meta-learning genetic programming. 2101-2102
• 
  José Parra Galaviz, Leonardo Trujillo, Patricia Melin: Backpropagation learning with a (1+1) ES. 2103-2104
• 
  Paulo Parracho, Rui Ferreira Neves, Nuno Horta: Trading in financial markets using pattern recognition optimized by genetic algorithms. 2105-2106
• 
  Marcin L. Pilat, Irene Pestov: Evolutionary computation on complex spatially-distributed networks. 2107-2108
• 
  Hari Prasain, Parimala Thulasiraman, Ruppa K. Thulasiram, Girish K. Jha: Particle swarm optimization algorithm for option pricing: extended abstract. 2109-2110
• 
  Yuji Sato, Hazuki Inoue: Genetic operations to solve sudoku puzzles. 2111-2112
• 
  Otávio Noura Teixeira, Felipe Houat de Brito, Walter Avelino da Luz Lobato, Artur Noura Teixeira, Carlos Takeshi Kudo Yasojima, Roberto Célio Limão de Oliveira: Fuzzy social interaction genetic algorithm. 2113-2114
• 
  Thanh-Do Tran, Gang-Gyoo Jin: Genetic algorithm with multi-colony dynamic reproduction. 2115-2116
• 
  Philip Valencia, Raja Jurdak, Peter Lindsay: Fitness importance for online evolution. 2117-2118
• 
  Zachary D. Williams, Gregory M. Kapfhammer: Using synthetic test suites to empirically compare search-based and greedy prioritizers. 2119-2120

Introductory tutorials

• 
  Erik D. Goodman: Introduction to genetic algorithms. 2121-2136
• 
  John R. Koza: Introduction to genetic programming tutorial: from the basics to human-competitive results. 2137-2262
• 
  Thomas Baeck: Evolution strategies: basic introduction. 2263-2288
• 
  Kenneth A. De Jong: Evolutionary computation: a unified approach. 2289-2302
• 
  Martin Pelikan: Probabilistic model-building genetic algorithms. 2303-2330
• 
  Martin V. Butz: Learning classifier systems. 2331-2352
• 
  Manuel López-Ibáñez: Ant colony optimization. 2353-2384
• 
  Conor Ryan: Grammatical evolution tutorial. 2385-2412
• 
  Mark Wineberg, Steffen Christensen: Statistical analysis for evolutionary computation: introduction. 2413-2440
• 
  Risto Miikkulainen: Evolving neural networks. 2441-2460
• 
  Christopher D. Clack: Financial evolutionary computing. 2461-2472

Advanced tutorials

• 
  Riccardo Poli: Genetic programming theory. 2473-2502
• 
  Jason H. Moore: Bioinformatics. 2503-2534
• 
  Franz Rothlauf: Representations for evolutionary algorithms. 2535-2556
• 
  Tobias Friedrich, Frank Neumann: Foundations of evolutionary multi-objective optimization. 2557-2576
• 
  Kalyanmoy Deb: Evolutionary multi-criterion optimization. 2577-2602
• 
  Carlos A. Coello Coello: Constraint-handling techniques used with evolutionary algorithms. 2603-2624
• 
  Thomas Bartz-Beielstein, Mike Preuss: Tuning and experimental analysis in evolutionary computation: what we still have wrong. 2625-2646
• 
  Michael D. Vose: Course notes: genetic algorithm theory. 2647-2660
• 
  Mark Wineberg, Steffen Christensen: Statistical analysis for evolutionary computation: advanced techniques. 2661-2682
• 
  Thomas Jansen, Frank Neumann: Computational complexity and evolutionary computation. 2683-2710

Specialized techniques and applications tutorials

• 
  Leonardo Vanneschi: Fitness landscapes and problem hardness in genetic programming. 2711-2738
• 
  Lee Spector: Evolution of quantum algorithms. 2739-2768
• 
  Sara Silva: Handling bloat in GP. 2769-2794
• 
  Carsten Witt: Theory of randomised search heuristics in combinatorial optimisation. 2795-2840
• 
  Kenneth O. Stanley: Generative and developmental systems. 2841-2862
• 
  Mark E. Kotanchek: Real-world data modeling. 2863-2896
• 
  Thomas Bäck, Joshua Knowles, Ofer M. Shir: Experimental optimization by evolutionary algorithms. 2897-2916
• 
  Benjamin E. Beckmann, Jeff Clune, Charles Ofria: Digital evolution with avida. 2917-2926
• 
  Julian Francis Miller, Simon L. Harding: Cartesian genetic programming. 2927-2948

last updated on Sat May 25 05:00:50 2013 by the dblp team
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