@techreport{TD:100135,
	att_abstract={{Random-key genetic algorithms were introduced by Bean (1994) for solving
sequencing problems in combinatorial optimization. Since then, they
have been extended to handle a wide class of combinatorial optimization
problems. This paper presents a tutorial on the implementation and
use of biased random-key genetic algorithms for solving combinatorial
optimization problems. Biased random-key genetic algorithms are a
variant of random-key genetic algorithms, where one of the parents
used for mating is biased to be of higher fitness than the other parent.
After introducing the basics of biased random-key genetic algorithms,
the paper discusses in some detail implementation issues, illustrating
the ease in which sequential and parallel heuristics based on biased
random-key genetic algorithms can be developed. A survey of applications
that have recently appeared in the literature is also given.
}},
	att_authors={mr5626},
	att_categories={C_CCF.1, C_CCF.2, C_CCF.7, C_CCF.8},
	att_copyright={{}},
	att_copyright_notice={{}},
	att_donotupload={true},
	att_private={false},
	att_projects={},
	att_tags={genetic algorithms,  biased random-key genetic algorithms,  random-key genetic algorithms,  combinatorial optimization,  metaheuristics},
	att_techdoc={true},
	att_techdoc_key={TD:100135},
	att_url={},
	author={Mauricio Resende and José Gonçalves},
	institution={{Journal of Heuristics}},
	month={August},
	title={{Biased random-key genetic algorithms for combinatorial optimization
}},
	year=2010,
}