@techreport{TD:5FE6RN,
	att_abstract={{Cellular manufacturing emerged as a production strategy capable of solving  the problems of complexity and long manufacturing lead times in batch  production. The fundamental problem in cellular manufacturing is the  formation of product families and machine cells. This paper presents a new  approach for obtaining machine cells and product families. The approach  combines a local search heuristic with a genetic algorithm. Computational  experience with the algorithm on a set of group technology problems  available in the literature is also presented. The approach produced  solutions with a grouping efficacy that is at least as good as any results  previously reported in literature and improved the grouping efficacy for  59 % of the problems. }},
	att_authors={mr5626},
	att_categories={},
	att_copyright={{}},
	att_copyright_notice={{}},
	att_donotupload={},
	att_private={false},
	att_projects={},
	att_tags={Cellular manufacturing, Random keys, Group technology, Genetic algorithms},
	att_techdoc={true},
	att_techdoc_key={TD:5FE6RN},
	att_url={http://web1.research.att.com:81/techdocs_downloads/TD:5FE6RN_DS1_2010-08-18T15:55:22.025Z.pdf},
	author={Mauricio Resende and José Gonçalves},
	institution={{}},
	month={October},
	title={{Hybrid genetic algorithm for manufacturing cell formation}},
	year=2002,
}