2008 | OriginalPaper | Buchkapitel
An Evolutionary Algorithm for the Block Stacking Problem
verfasst von : Tim Hohm, Matthias Egli, Samuel Gaehwiler, Stefan Bleuler, Jonathan Feller, Damian Frick, Richard Huber, Mathias Karlsson, Reto Lingenhag, Thomas Ruetimann, Tom Sasse, Thomas Steiner, Janine Stocker, Eckart Zitzler
Erschienen in: Artificial Evolution
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
How has a stack of
n
blocks to be arranged in order to maximize its overhang over a table edge while being stable? This question can be seen as an example application for applied statics and at the same time leads to a challenging optimization problem that was discussed recently in two theoretical studies.
Here, we address this problem by designing an evolutionary algorithm; the proposed method is applied to two instances of the block stacking problem, maximizing the overhang for 20 and 50 block stacks. The study demonstrates that the stacking problem is worthwhile to be investigated in the context of randomized search algorithms: it represents an abstract, but still demanding instance of many real-world applications. Furthermore, the proposed algorithm may become useful in empirically testing the tightness of theoretical upper bounds proposed for this problem.