Rough set theory over two universes is a generalization of rough set model to find
accurate approximations for uncertain concepts in information systems in which
uncertainty arises from existence of interrelations between the three basic sets:
objects, attributes, and decisions.
In this work, multisets are approximated in a crisp two-universe approximation space
using binary ordinary relation and multi relation. The concept of two universe
approximation is applied for defining lower and upper approximations of multisets.
Properties of these approximations are investigated, and the deviations between
them and corresponding notions are obtained; some counter examples are given.
The suggested notions can help in the modification of the decision-making for
events in which objects have repetitions such as patients visiting a doctor more than
one time; an example for this case is given.