Comparison of two metaheuristics to solve a 2-D cutting stock problem with set-up cost in the paper industry. (2016)

• Record Type: Journal Article
• Authors: Bonnevay, Stéphane; Gavin, Gérald; Aubertin, Philippe
• Is Part Of: International journal of metaheuristics. Volume 5:Number 1(2016)
• Page Start: 31
• Page End: 50
• Publication Date: 2016
• Subjects: combinatorial optimisation -- genetic algorithms -- metaheuristics -- paper industry -- setup costs -- simulated annealing -- 2D CSP -- cutting stock problem -- bin packing -- linear programming; Heuristic algorithms -- Periodicals; 006.3105
• Languages: English
• ISSNs: 1755-2176

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.