  In many real-world applications, the Pareto Set (PS) of a continuous
multiobjective optimization problem can be a piecewise continuous manifold. A
decision maker may want to find a solution set that approximates a small part
of the PS and requires the solutions in this set share some similarities. This
paper makes a first attempt to address this issue. We first develop a
performance metric that considers both optimality and variable sharing. Then we
design an algorithm for finding the model that minimizes the metric to meet the
user's requirements. Experimental results illustrate that we can obtain a
linear model that approximates the mapping from the preference vectors to
solutions in a local area well.
