@techreport{TD:101126,
	att_abstract={{This paper describes LIBBRKGA, a GNU-style dynamic shared Python/C++
library of the biased random-key genetic algorithm (BRKGA) for bound
constrained global optimization.  BRKGA (Gonçalves ad Resende, 2011) is a
general search metaheuristic for finding optimal or near-optimal solutions
to hard optimization problems.  It is derived from the random-key
genetic algorithm of BEAN (1994), differing in the way solutions are
combined to produce offspring.  After a brief introduction to BRKGA,
we show how to download, install, configure, and use the library through
an illustrative example.
}},
	att_authors={mr5626},
	att_categories={C_CCF.7, C_CCF.8, C_CCF.2},
	att_copyright={{Springer Science+Business Media}},
	att_copyright_notice={{The definitive version was published in   2013. {{, 2013-10-05}}{{, 10.1007/s10878-013-9659-z}}
}},
	att_donotupload={},
	att_private={false},
	att_projects={},
	att_tags={Biased random-key genetic algorithm,  global optimization,  multimodal functions,  continuous optimization,  heuristic,  stochastic algorithm,  stochastic local search,  nonlinear programming.},
	att_techdoc={true},
	att_techdoc_key={TD:101126},
	att_url={http://web1.research.att.com:81/techdocs_downloads/TD:101126_DS1_2013-03-01T17:31:41.081Z.pdf},
	author={Mauricio Resende and Ricardo M.A. Silva, Fed. U. of Pernambuco and Panos M. Pardalos},
	institution={{J. of Combinatorial Optimization}},
	month={October},
	title={{A Python/C++ library for bound-constrained global optimization
using biased random-key genetic algorithm
}},
	year=2013,
}