An effective solution for a real cutting stock problem in manufacturing plastic rolls
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We confront a practical cutting stock problem from a production plant of plastic rolls. The problem is a variant of the well-known one dimensional cutting stock, with particular constraints and optimization criteria defined by the experts of the company. We start by giving a problem formulation in which optimization criteria have been considered in linear hierarchy according to expert preferences, and then propose a heuristic solution based on a GRASP algorithm. The generation phase of this algorithm solves a simplified version which is rather similar to the conventional one dimensional cutting stock. To do that, we propose a Sequential Heuristic Randomized Procedure (SHRP). Then in the repairing phase, the solution of the simplified problem is transformed into a solution to the real problem. For experimental study we have chosen a set of problem instances of com-mon use to compare SHRP with another recent approach. Also, we show by means of examples, how our approach works over instances taken from the real production process.
KeywordsCutting stock Iterative sequential heuristics Randomized algorithms Meta-heuristics Multi-objective optimization
- Belov, G., & Scheithauer, G. (2003). The number of setups (different patterns) in one-dimensional stock cutting. Technical Report, Desden University. Google Scholar
- Foerster, H., & Wäscher, G. (1999). Pattern reduction in one-dimensional cutting stock problems. In Proceedings of the 15th trienal conference of the international federation of operational research societies. Google Scholar
- Johnston, R. E. (1986). Rounding algorithm for cutting stock problems. Journal of Asian-Pacific Operations Research societies, 3, 166–171. Google Scholar
- Resende, M., & Ribeiro, G. (2002). Greedy randomized adaptive search procedures (pp. 219–249). Dordrecht: Kluwer Academic. Google Scholar