COCO - COmparing Continuous Optimizers : The Documentation

COmparing Continuous Optimisers (COCO) is a tool for benchmarking algorithms for black-box optimisation. COCO facilitates systematic experimentation in the field of continuous optimization. COCO provides an experimental framework for testing the algorithms, post-processing facilities for generating publication-quality figures and tables, LaTeX templates of articles which present the figures and tables in a single document.

[1]  K. Price Differential evolution vs. the functions of the 2/sup nd/ ICEO , 1997, Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97).

[2]  Thomas Stützle,et al.  Evaluating Las Vegas Algorithms: Pitfalls and Remedies , 1998, UAI.

[3]  Fernando G. Lobo,et al.  A parameter-less genetic algorithm , 1999, GECCO.

[4]  Nikolaus Hansen,et al.  A restart CMA evolution strategy with increasing population size , 2005, 2005 IEEE Congress on Evolutionary Computation.

[5]  Anne Auger,et al.  Performance evaluation of an advanced local search evolutionary algorithm , 2005, 2005 IEEE Congress on Evolutionary Computation.

[6]  Vitaliy Feoktistov Differential Evolution: In Search of Solutions , 2006 .

[7]  M. Kenward,et al.  An Introduction to the Bootstrap , 2007 .