Franz Rothlauf: Genetic and Evolutionary Computation Conference, GECCO 2009, Proceedings, Montreal, Québec, Canada, July 8-12, 2009, Companion Material.ACM2009, ISBN 978-1-60558-505-5
Late-breaking papers
Adrian K. Agogino: Evaluating evolution and monte carlo for controlling air traffic flow.1957-1962
Wei Cui, Anthony Brabazon, Michael O'Neill: Efficient trade execution using a genetic algorithm in an order book based artificial stock market.2023-2028
Jonatan Gómez, Roberto Poveda, Elizabeth León: Grisland: a parallel genetic algorithm for finding near optimal solutions to the traveling salesman problem.2035-2040
Daniel Molina, Manuel Lozano, Francisco Herrera: A memetic algorithm using local search chaining forblack-box optimization benchmarking 2009 for noise free functions.2255-2262
Mohammed El-Abd, Mohamed S. Kamel: Black-box optimization benchmarking for noiseless function testbed using an EDA and PSO hybrid.2263-2268
Mohammed El-Abd, Mohamed S. Kamel: Black-box optimization benchmarking for noiseless function testbed using particle swarm optimization.2269-2274
Mohammed El-Abd, Mohamed S. Kamel: Black-box optimization benchmarking for noiseless function testbed using PSO_bounds.2275-2280
Marcus Gallagher: Black-box optimization benchmarking: results for the BayEDAcG algorithm on the noiseless function testbed.2281-2286
Carlos García-Martínez, Manuel Lozano: A continuous variable neighbourhood search based on specialised EAs: application to the noiseless BBO-benchmark 2009.2287-2294
Peter Korosec, Jurij Silc: A stigmergy-based algorithm for black-box optimization: noiseless function testbed.2295-2302
Jirí Kubalík: Black-box optimization benchmarking of prototype optimization with evolved improvement steps for noiseless function testbed.2303-2308
Petr Posik: BBOB-benchmarking a simple estimation of distribution algorithm with cauchy distribution.2309-2314
Petr Posik: BBOB-benchmarking the DIRECT global optimization algorithm.2315-2320
Petr Posik: BBOB-benchmarking the generalized generation gap model with parent centric crossover.2321-2328
Petr Posik: BBOB-benchmarking two variants of the line-search algorithm.2329-2336
Petr Posik: BBOB-benchmarking the Rosenbrock's local search algorithm.2337-2342
Carlos García-Martínez, Manuel Lozano: A continuous variable neighbourhood search based on specialised eas: application to the noisy BBO-benchmark 2009 testbed.2367-2374
Peter Korosec, Jurij Silc: A stigmergy-based algorithm for black-box optimization: noisy function testbed.2375-2382
Marcus R. Gallagher: Black-box optimization benchmarking: results for the BayEDAcG algorithm on the noisy function testbed.2383-2388
Nikolaus Hansen: Benchmarking a BI-population CMA-ES on the BBOB-2009 function testbed.2389-2396
Nikolaus Hansen: Benchmarking a BI-population CMA-ES on the BBOB-2009 noisy testbed.2397-2402
Nikolaus Hansen: Benchmarking the nelder-mead downhill simplex algorithm with many local restarts.2403-2408
Raymond Ros: Benchmarking the BFGS algorithm on the BBOB-2009 function testbed.2409-2414
Raymond Ros: Benchmarking the BFGS algorithm on the BBOB-2009 noisy testbed.2415-2420
Raymond Ros: Benchmarking the NEWUOA on the BBOB-2009 function testbed.2421-2428
Raymond Ros: Benchmarking the NEWUOA on the BBOB-2009 noisy testbed.2429-2434
Raymond Ros: Benchmarking sep-CMA-ES on the BBOB-2009 function testbed.2435-2440
Raymond Ros: Benchmarking sep-CMA-ES on the BBOB-2009 noisy testbed.2441-2446
Anne Auger: Benchmarking the (1+1) evolution strategy with one-fifth success rule on the BBOB-2009 function testbed.2447-2452
Anne Auger: Benchmarking the (1+1)-ES with one-fifth success rule on the BBOB-2009 noisy testbed.2453-2458
Anne Auger, Nikolaus Hansen: Benchmarking the (1+1)-CMA-ES on the BBOB-2009 function testbed.2459-2466
Ajay Kumar Tanwani, Muddassar Farooq: Performance evaluation of evolutionary algorithms in classification of biomedical datasets.2617-2624
Richard Preen: An XCS approach to forecasting financial time series.2625-2632
Alexander Scheidler, Martin Middendorf: Evolved cooperation and emergent communication structures in learning classifier based organic computing systems.2633-2640
Learning from failures in evolutionary computation (LFFEC)
Mustafa Safdari: Evolving universal hash functions using genetic algorithms.2729-2732
Josh Glascock, Brian Hunter: Minimizing total completion time in two-machine flow shops with exact delay using genetic algorithm & ant colony algorithm.2733-2736