A Restricted Dual Peaceman-Rachford Splitting Method for 
a Strengthened DNN Relaxation for QAP

ABSTRACT:
Splitting methods in optimization arise when one can divide an
optimization problem into two or more simpler subproblems. They have proven
particularly successful for relaxations of problems involving 
discrete variables. We revisit and strengthen splitting methods for solving
doubly nonnegative, DNN, relaxations of the particularly difficult,
NP-hard quadratic assignment problem, QAP. 
We use a modified restricted contractive splitting method,
PRSM, approach. In particular, we show how to exploit redundant
constraints in the subproblems. Our strengthened bounds exploit these new 
subproblems, as well as new dual multiplier estimates, to
improve on the bounds and convergence results in the literature.