Journal
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
Volume 145, Issue 2, Pages 500-510Publisher
ELSEVIER
DOI: 10.1016/j.ijpe.2013.04.019
Keywords
Bin packing; Genetic algorithm; Three-dimensional; Random keys
Categories
Funding
- ERDF through the Programme COMPETE
- Portuguese Government through FCT - Foundation for Science and Technology [PTDC/EGE-GES/117692/2010]
- Fundação para a Ciência e a Tecnologia [PTDC/EGE-GES/117692/2010] Funding Source: FCT
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In this paper we present a novel biased random-key genetic algorithm (BRKGA) for 2D and 3D bin packing problems. The approach uses a maximal-space representation to manage the free spaces in the bins. The proposed algorithm hybridizes a novel placement procedure with a genetic algorithm based on random keys. The BRKGA is used to evolve the order in which the boxes are packed into the bins and the parameters used by the placement procedure. Two new placement heuristics are used to determine the bin and the free maximal space where each box is placed. A novel fitness function that improves significantly the solution quality is also developed. The new approach is extensively tested on 858 problem instances and compared with other approaches published in the literature. The computational experiment results demonstrate that the new approach consistently equals or outperforms the other approaches and the statistical analysis confirms that the approach is significantly better than all the other approaches. (C) 2013 Elsevier B.V. All rights reserved.
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