  Blind source separation (BSS) methods have been applied to deal with the lack
of selectivity of ion-selective electrodes (ISE). In this paper, differently
from the standard BSS solutions, which are based on the optimization of a
mono-objective cost function associated with a given property of the sought
signals, we introduce a novel approach by relying on multi-objective
optimization. Numerical experiments with actual data attested that our proposal
allows the incorporation of additional information on the interference model
and also provides the user a set of solutions from which he/she can select a
proper one according to his/her prior knowledge on the problem.
