A Hybrid Genetic Algorithm for Optimization of Two-dimensional Cutting-Stock Problem

Ahmed Mellouli, Faouzi Masmoudi, Imed Kacem and Mohamed Haddar
Additional contact information
Ahmed Mellouli: University of Sfax, Tunisia
Faouzi Masmoudi: University of Sfax, Tunisia
Imed Kacem: University Paul Verlaine - Metz, LITA, France
Mohamed Haddar: University of Sfax, Tunisia

International Journal of Applied Metaheuristic Computing (IJAMC), 2010, vol. 1, issue 2, 34-49

Abstract: In this paper, the authors present a hybrid genetic approach for the two-dimensional rectangular guillotine oriented cutting-stock problem. In this method, the genetic algorithm is used to select a set of cutting patterns while the linear programming model permits one to create the lengths to produce with each cutting pattern to fulfil the customer orders with minimal production cost. The effectiveness of the hybrid genetic approach has been evaluated through a set of instances which are both randomly generated and collected from the literature.

Date: 2010
References: Add references at CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 4018/jamc.2010040103 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jamc00:v:1:y:2010:i:2:p:34-49

Access Statistics for this article

International Journal of Applied Metaheuristic Computing (IJAMC) is currently edited by Peng-Yeng Yin

More articles in International Journal of Applied Metaheuristic Computing (IJAMC) from IGI Global
Bibliographic data for series maintained by Journal Editor ().