Descent search approaches applied to the minimization of open stacks.
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2017
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Resumo
In this paper, new algorithms are proposed for solving the minimization of open stacks, an industrial cutting
pattern sequencing problem. In the considered context, the objective is to minimize the use of intermediate
storage, as well as the unnecessary handling of manufactured products. We introduce a new
local search method, specifically tailored for this NP-hard problem, which has wide practical applications.
In order to further explore the solution space, we use this new local search as a component in
two descent search methods associated with grouping strategies: variable neighborhood descent and
steepest descent. Computational experiments were conducted involving 595 benchmark instances from
five different sets through which the contributions of the proposed methods were compared with those
of the state-of-the-art methods. The results demonstrate that the proposed algorithms are competitive
and robust, as high quality solutions were consistently generated in a reasonable running time.
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Scheduling, Minimization of open stacks, Variable neighborhood descent
Citação
LIMA, J. R.; CARVALHO, M. A. M. de. Descent search approaches applied to the minimization of open stacks. Computers & Industrial Engineering, v. 112, p. 175-186, 2017. Disponível em: <http://www.sciencedirect.com/science/article/pii/S0360835217303741>. Acesso em: 16 jan. 2018.