An effective solution for a real cutting stock problem in manufacturing plastic rolls

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. All authors are supported by MEC-FEDER Grant TIN2007-67466-C02-01 and by contract CN-05-127 of the University of Oviedo and the company ERVISA, and by FICYT under grant BP04-021. Ramiro Varela · Camino R. Vela · Jorge Puente Computing Technologies Group. Department of Computing, Artificial Intelligence Center, University of Oviedo, Spain. Campus de Viesques, 33271 Gijón. Ramiro Varela E-mail: [email protected] Camino R. Vela E-mail: [email protected] Jorge Puente E-mail: [email protected] Maŕıa Sierra · Inés González-Rodŕıguez Department of Mathematics, Statistics and Computing. University of Cantabria, Spain. Los Castros s/n, 39005 Santander. Maŕıa Sierra E-mail: [email protected] Inés González-Rodŕıguez E-mail: [email protected]