Abstract
We investigate a variant of the bin packing problem in which items may be fragmented into smaller size pieces called fragments. While there are a few applications to bin packing with item fragmentation, our model of the problem is derived from a scheduling problem present in data over CATV networks. Fragmenting an item is associated with a cost which renders the problem NP-hard. We study two possible cost functions and as a result get two variants of bin packing with item fragmentation. In the first variant, called bin packing with size-increasing fragmentation, each item may be fragmented in which case overhead units are added to the size of every fragment. In the second variant each item has a size and a cost and fragmenting an item increases its cost but does not change its size. We call this variant bin packing with size-preserving fragmentation.
We develop several algorithms for the problem and investigate their performance. The algorithms we present are based on well known bin packing algorithms such as Next-Fit and First-Fit Decreasing, as well as of other algorithms...
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Menakerman, N., Rom, R. (2001). Bin Packing with Item Fragmentation. In: Dehne, F., Sack, JR., Tamassia, R. (eds) Algorithms and Data Structures. WADS 2001. Lecture Notes in Computer Science, vol 2125. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44634-6_29
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DOI: https://doi.org/10.1007/3-540-44634-6_29
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