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Ingeniare. Revista chilena de ingeniería

versión On-line ISSN 0718-3305

Ingeniare. Rev. chil. ing. v.16 n.3 Arica dic. 2008

http://dx.doi.org/10.4067/S0718-33052008000300005 

 

Ingeniare. Revista chilena de ingeniería, vol. 16 Nº 3, 2008, pp. 421-427


A GRASP METAHEURISTIC FOR THE ORDERED CUTTING STOCK PROBLEM


UN METAHEURÍSTICO GRASP PARA EL PROBLEMA DE STOCK DE CORTE ORDENADO

 
Rodrigo Rabello Golfeto1                   Antônio Carlos Moretti2                   Luiz Leduíno de Salles Neto3

1 Universidade Federal Fluminense. Departamento de Ciência da Computação. Avenida dos Trabalhadores, 420, Vila Santa Cecília, 27255-250, Volta Redonda. Rio de Janeiro, Brasil. Email: rodrigo.golfeto@gmail.com
2 Universidade Estadual de Campinas. Departamento de Matemática Aplicada. Rua Sergio Buarque de Holanda, 651, Cidade Universitária - Barão Geraldo Caixa Postal: 6065, 13083-859. Campinas, São Paulo, Brasil. E-mail: moretti@ime.unicamp.br
3 Universidade Federal de São Paulo. Departamento de Ciência y Tecnologia. Avenida Mário Covas, 610, 12231-280. São José dos Campos, São Paulo, Brasil. E-mail: luiz.leduino@unifesp.br


RESUMEN 

Este estudio presenta un nuevo modelo matemático y un procedimiento meta-heurístico de búsqueda voraz adaptativa y aleatoria (GRASP, por sus siglas en inglés) para resolver el problema de stock de corte ordenado. Éste problema ha sido introducido recientemente en la literatura. Es apropiado minimizar la materia prima usada por las industrias que manipulan inventarios reducidos de productos, tales como las industrias que usan la base justo a tiempo para su producción. En tales casos, los modelos clásicos para resolver el problema de stock de corte ordenado son inútiles. Los resultados obtenidos, mediante experimentos computacionales para un conjunto de ejemplos aleatorios, demuestran que el método propuesto puede ser aplicado a industrias grandes que procesan cortes en sus líneas de producción y no mantienen en stock sus productos.

Palabras clave: Problemas de stock de corte, GRASP, Just-in-time.

 
ABSTRACT  

This study presents a new mathematical model and a Greedy Randomized Adaptive Search Procedure (GRASP) meta-heuristic to solve the ordered cutting stock problem. The ordered cutting stock problem was recently introduced in literature. It is appropriate to minimize the raw material used by industries that deal with reduced product inventories, such as industries that use the just-in-time basis for their production. In such cases, classic models for solving the cutting stock problem are useless. Results obtained from computational experiments for a set of random instances demonstrate that the proposed method can be applied to large industries that process cuts on their production lines and do not stock their products. 

Keywords: Cutting Stock problem, GRASP, Just-in-time.  


ACKNOWLEDGEMENTS 

The authors have been partially supported by M.E.C. (Spain), Project MTM2007-063432. The second author is also supported by CNPq (Brazil), Project 307907/2007-4.  


 

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Received June 19, 2008 Accepted December 5, 2008

 

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