INTELCSP: computational intelligence applied to cutting stock problems
by Rodrigo Rabello Golfeto; Antônio Carlos Moretti; Luiz Leduíno De Salles Neto
International Journal of Computational Intelligence Studies (IJCISTUDIES), Vol. 1, No. 4, 2012

Abstract: This study presents the promising results obtained for an intelligent decision-making system for industrial processes in which the cutting stock problem is a component relevant to production planning. In order to establish a cutting process assisted by an intelligent system, with memory and learning capabilities, we utilised a symbiotic genetic algorithm (Symbio) that we developed for cutting stock problems with multiple objectives, setup costs and waste. We used case-based reasoning (CBR) as a learning strategy. The results obtained show that this is a promising approach.

Online publication date: Thu, 28-Aug-2014

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