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Heuristics for the variable sized bin-packing problem
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DOI：10.1016/j.cor.2008.12.016.png)
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Abstract
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We investigate the one-dimensional variable-sized bin-packing problem. This problem requires packing a set of items into a minimum-cost set of bins of unequal sizes and costs. Six optimization-based heuristics for this problem are presented and compared. We analyze their empirical performance on a large set of randomly generated test instances with up to 2000 items and seven bin types. The first contribution of this paper is to provide evidence that a set covering heuristic proves to be highly effective and capable of delivering very-high quality solutions within short CPU times. In addition, we found that a simple subset-sum problem-based heuristic consistently outperforms heuristics from the literature while requiring extremely short CPU times. (C) 2009 Elsevier Ltd. All rights reserved.
Keywords:
Bin-packing problem
Heuristics
Genetic algorithm
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