Application of a Hybrid Genetic Algorithm for cutting with particular stockKos, Leon, 1966- ; Jelić, Nikola ; Duhovnik, Jože, 1948-The paper presents approach to solve a problem of optimum cutting with the particular stock. This problem has already been tackled via developing and applying a first version of the Hybrid Grouping ... Genetic Algorithm (HGGA) code (Kos and Duhovnik, 2002) employed in the opti-mum cutting plan. It turned out that the slightly upgraded version of the code show a wider applicability and can apply to many problems of practical interest like cutting, packing, produc-tion scheduling, and planning. Many production environments entail additional requirements that should be weighted during the search for an optimum solution. We present the motivation, flowchart and capabilities of thecode and results obtained on a case of interest, i.e., we have shown how the hybrid genetic algorithm can be used as heuristics which, provides qualitypack-ing for cutting large items. The problem can be effectively tackled, provided practical require-ments and limitations are taken into consideration. Domain-specific knowledge and local hill-climbing in the genetic algorithm has turned out to be helpful in many aspects of the optimization process. The HGGA presented is robust and easy to use, as there are only few parameters with a large range of successful operation. Directions for possible future developments are discussed.Vir: Advances in simulation-based decision support. Volume II (Str. 21-25)Vrsta gradiva - prispevek na konferenciLeto - 2011Jezik - angleškiCOBISS.SI-ID - 12067611
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