Title: INTELCSP: computational intelligence applied to cutting stock problems

Authors: Rodrigo Rabello Golfeto; Antônio Carlos Moretti; Luiz Leduíno De Salles Neto

Addresses: Production Engineering Department, Fluminense Federal University, Avenida dos Trabalhadores, 420, Vila Santa Cecília, Volta Redonda, RJ, 27255-970, Brazil. ' Institute of Mathematics, Statistics and Scientific Computation, State University of Campinas, Cidade Universitária Zeferino Vaz, s/n, Barão Geraldo, Campinas, SP, 13084-790, Brazil. ' Department of Science and Technology, Federal University of São Paulo, Avenida Mário Covas, 610, Vila Nair, São José dos Campos, SP, Brazil

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.

Keywords: cutting stock problem; CSP; genetic algorithms; symbiosis; artificial intelligence; case-based reasoning; CBR; computational intelligence; intelligent decision making; production planning.

DOI: 10.1504/IJCISTUDIES.2012.050354

International Journal of Computational Intelligence Studies, 2012 Vol.1 No.4, pp.312 - 321

Received: 17 Jan 2012
Accepted: 08 Feb 2012
Published online: 28 Aug 2014 *

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