  We propose a new variant of Chubanov's method for solving the feasibility
problem over the symmetric cone by extending Roos's method (2018) of solving
the feasibility problem over the nonnegative orthant. The proposed method
considers a feasibility problem associated with a norm induced by the maximum
eigenvalue of an element and uses a rescaling focusing on the upper bound for
the sum of eigenvalues of any feasible solution to the problem. Its
computational bound is (i) equivalent to that of Roos's original method (2018)
and superior to that of Louren\c{c}o et al.'s method (2019) when the symmetric
cone is the nonnegative orthant, (ii) superior to that of Louren\c{c}o et al.'s
method (2019) when the symmetric cone is a Cartesian product of second-order
cones, (iii) equivalent to that of Louren\c{c}o et al.'s method (2019) when the
symmetric cone is the simple positive semidefinite cone, and (iv) superior to
that of Pena and Soheili's method (2017) for any simple symmetric cones under
the feasibility assumption of the problem imposed in Pena and Soheili's method
(2017). We also conduct numerical experiments that compare the performance of
our method with existing methods by generating instances in three types:
strongly (but ill-conditioned) feasible instances, weakly feasible instances,
and infeasible instances. For any of these instances, the proposed method is
rather more efficient than the existing methods in terms of accuracy and
execution time.
