We introduce the strongly NP-complete pagination problem, an extension of Bin Packing where packing together two 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: while, in Bin Packing, any two such sets would be dis-joint, in Pagination, they can share zero, one or more symbols. After formulating the problem 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 pre-dictive measure of the difficulty of a given instance, and finally recommend which algorithm should be used in which case, depending on either time constraints or quality requirements.