An Evolutionary Algorithm for 2D Semi-Guillotinable Circular Saw Cutting

0384758 - ÚI 2013 RIV US eng C - Conference Paper (international conference)
Balcar, S. - Pilát, M. - Neruda, Roman
An Evolutionary Algorithm for 2D Semi-Guillotinable Circular Saw Cutting.
CEC 2012. Proceedings of IEEE Congress on Evolutionary Computation. Piscataway: IEEE, 2012, s. 1-5. ISBN 978-1-4673-1509-8.
[CEC 2012. IEEE Congress on Evolutionary Computation. Brisbane (AU), 10.06.2012-15.06.2012]
R&D Projects: GA MŠMT OC10047
Institutional support: RVO:67985807
Keywords : genetic algorithms * cutting problem * computational intelligence
Subject RIV: IN - Informatics, Computer Science

We define a new class of 2D-stock cutting problems, the so called semi-quillotinable problems, and show its practical importance in solving the task of creating optimal cutting plans for a circular saw. Furthermore, we create a new algorithm suited for solving of semi-guillotinable problems by adapting existing evolutionary algorithms for both guillotinable and non-guillotinable 2D stock cutting problems. This algorithm is compared to standard algorithms on a selected set of both benchmark and real-life problems.
Permanent Link: http://hdl.handle.net/11104/0007326