Use of genetic algorithms for solving problems of optimal cutting

Cutting and packing problem is one of the most common optimization problem. Even a small space or material savings allow obtaining substantial advantages on an industrial scale. This paper proposes the genetic algorithm to solve this problem. It includes multipoint operators of crossing, mutation an...

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Bibliographic Details
Published in:ITM web of conferences 2016, Vol.6, p.2008
Main Authors: Sergievskiy, Maxim, Syroezhkin, Sergey
Format: Article
Language:English
Subjects:
Algorithms
Cutting
Dependence
Genetic algorithms
Operators
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Summary:Cutting and packing problem is one of the most common optimization problem. Even a small space or material savings allow obtaining substantial advantages on an industrial scale. This paper proposes the genetic algorithm to solve this problem. It includes multipoint operators of crossing, mutation and selection. To use these operators, the special encoding of cutting card is applied, that can be transformed to the real coordinates by using decoder. This is a block typed decoder, which substitution strategy is “first-fit”. Efficiency of the solutions, obtained by the algorithm, depends on its parameters and on dimension of a task, but on average it decreases under the logarithmic law from dimension of a task. Temporary complexity of algorithm shows square dependence on the task dimension.
ISSN:2271-2097
2431-7578
2271-2097
DOI:10.1051/itmconf/20160602008