Haouari, MohamedSerairi, M.2012-05-312012-05-312009-100305-0548http://hdl.handle.net/10679/189https://doi.org/10.1016/j.cor.2008.12.016Due to copyright restrictions, the access to the full text of this article is only available via subscription.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 requir- ing extremely short CPU times.engrestrictedAccessarticle36102877288400026536920002010.1016/j.cor.2008.12.016Bin-packing problemHeuristicsGenetic algorithm2-s2.0-62549163791