Algorithms for the bin packing problem with overlapping items

•This work focus on a Bin Packing where items are sets which may share elements.•This is the same problem as VM-Packing, but without domain specific constraints.•Several heuristics are studied, both theoretically and experimentally. We study an extension of the bin packing problem, where packing together two or more items may make them occupy less volume than the sum of their individual sizes. To achieve this property, an item is defined as a finite set of symbols from a given alphabet. Unlike the items of Bin Packing, two such sets can share zero, one or more symbols. The problem was first introduced by Sindelar et al. (2011) under the name of VM Packing with the addition of hierarchical sharing constraints making it suitable for virtual machine colocation. Without these constraints, we prefer the more general name of Pagination. After formulating it as an integer linear program, we try to approximate its solutions with several families of algorithms: from straightforward adaptations of classical Bin Packing heuristics, to dedicated algorithms (greedy and non-greedy), to standard and grouping genetic algorithms. All of them are studied first theoretically, then experimentally on an extensive random test set. Based upon these data, we propose a predictive measure of the statistical difficulty of a given instance, and finally recommend which algorithm should be used in which case, depending on either time constraints or quality requirements.