Entrepôts, Représentation et Ingénierie des Connaissances
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- Comparison of two metaheuristics to solve a 2-D cutting stock problem with setup cost in the paper industry doi link

Author(s): Bonnevay S.(Corresp.), Gavin G., Aubertin P.

(Article) Published: International Journal Of Metaheuristics, vol. 5 p.31-50 (2016)


DOI: 10.1504/IJMHEUR.2016.079107
Abstract:

This paper deals with the Two-Dimensional Cutting Stock Problem with Setup Cost (2CSP-S). This problem is composed of three optimization 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 realized on real and artificial datasets.