Comparison of two metaheuristics to solve a 2-D cutting stock problem with set-up cost in the paper industry Online publication date: Mon, 12-Sep-2016
by Stéphane Bonnevay; Gérald Gavin; Philippe Aubertin
International Journal of Metaheuristics (IJMHEUR), Vol. 5, No. 1, 2016
Abstract: This paper deals with the two-dimensional cutting stock problem with set-up cost (2CSP-S). This problem is composed of three optimisation sub-problems: a 2-D bin packing (2BP) problem (to place images on patterns), a linear programming (LP) problem (to find for each pattern the number of stock sheets to be printed) and a combinatorial problem (to find the number of each image on each pattern). We have already developed two different metaheuristics to solve the 2CSP-S focusing on this third sub-problem: a simulated annealing and a genetic algorithm. In this article, we propose to compare these two approaches. It is important to notice that our approaches are not new packing techniques. This work was conducted for a paper industry company and experiments were realised on real and artificial data sets.
Online publication date: Mon, 12-Sep-2016
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