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

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

Ahmed Mellouli, Faouzi Masmoudi, Imed Kacem, Mohamed Haddar
Copyright: © 2010 |Volume: 1 |Issue: 2 |Pages: 16
ISSN: 1947-8283|EISSN: 1947-8291|EISBN13: 9781609604264|DOI: 10.4018/jamc.2010040103
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MLA

Mellouli, Ahmed, et al. "A Hybrid Genetic Algorithm for Optimization of Two-dimensional Cutting-Stock Problem." IJAMC vol.1, no.2 2010: pp.34-49. http://doi.org/10.4018/jamc.2010040103

APA

Mellouli, A., Masmoudi, F., Kacem, I., & Haddar, M. (2010). A Hybrid Genetic Algorithm for Optimization of Two-dimensional Cutting-Stock Problem. International Journal of Applied Metaheuristic Computing (IJAMC), 1(2), 34-49. http://doi.org/10.4018/jamc.2010040103

Chicago

Mellouli, Ahmed, et al. "A Hybrid Genetic Algorithm for Optimization of Two-dimensional Cutting-Stock Problem," International Journal of Applied Metaheuristic Computing (IJAMC) 1, no.2: 34-49. http://doi.org/10.4018/jamc.2010040103

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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.

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