  In this paper, a new upper bound for the Multiple Knapsack Problem (MKP) is
proposed, based on the idea of relaxing MKP to a {\em Bounded Sequential
Multiple Knapsack Problem}, i.e., a multiple knapsack problem in which item
sizes are divisible. Such a relaxation, called sequential relaxation, is
obtained by suitably replacing the items of a MKP instance with items with
divisible sizes. Experimental results on benchmark instances show that the
upper bound is effective when the ratio between the number of items and the
number of knapsacks is small.
