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A Hybrid Genetic Algorithm for Optimization of Two-Dimensional Cutting-Stock Problem
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Author(s): Ahmed Mellouli (University of Sfax, Tunisia), Faouzi Masmoudi (University of Sfax, Tunisia), Imed Kacem (University Paul Verlaine - Metz, LITA, France)and Mohamed Haddar (University of Sfax, Tunisia)
Copyright: 2012
Pages: 16
Source title:
Modeling, Analysis, and Applications in Metaheuristic Computing: Advancements and Trends
Source Author(s)/Editor(s): Peng-Yeng Yin (Ming Chuan University, Taiwan)
DOI: 10.4018/978-1-4666-0270-0.ch004
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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 fulfill 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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