Araujo, Silvio Alexandre de [UNESP]Poldi, Kelly CristinaSmith, Jim2015-02-022015-02-022014-05-01Pesquisa Operacional. Sociedade Brasileira de Pesquisa Operacional, v. 34, n. 2, p. 165-187, 2014.0101-7438http://hdl.handle.net/11449/114164This paper investigates the one-dimensional cutting stock problem considering two conflicting objective functions: minimization of both the number of objects and the number of different cutting patterns used. A new heuristic method based on the concepts of genetic algorithms is proposed to solve the problem. This heuristic is empirically analyzed by solving randomly generated instances and also practical instances from a chemical-fiber company. The computational results show that the method is efficient and obtains positive results when compared to other methods from the literature.165-187enginteger optimizationcutting stock problem with setupsgenetic algorithmArtigo10.1590/0101-7438.2014.034.02.0165S0101-74382014000200165Acesso abertoS0101-74382014000200165.pdf99197731823160620000-0002-4762-2048