1. A machine learning approach for automated strip packing algorithm selection.
- Author
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Rakotonirainy, R. G.
- Subjects
- *
MACHINE learning , *METAHEURISTIC algorithms , *DATA mining , *ALGORITHMS - Abstract
This paper deals with strip packing metaheuristic algorithm selection using data mining techniques. Given a set of solved strip packing problem instances, the relationship between the instance characteristics and algorithm performance is learned and is used to predict the best algorithms to solve a new set of unseen problem instances. A framework capable of modelling this relationship for an automated packing algorithm selection is proposed. The effectiveness of the proposed framework is evaluated in the context of a large set of strip packing problem instances and the state-of-the-art strip packing algorithms. The results suggest a 91% accuracy in correctly identifying the best algorithm for a given instance. [ABSTRACT FROM AUTHOR]
- Published
- 2020
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