A new lower bound via projection for the quadratic assignment problem
Mathematics of Operations Research
P-Complete Approximation Problems
Journal of the ACM (JACM)
On Lagrangian Relaxation of Quadratic Matrix Constraints
SIAM Journal on Matrix Analysis and Applications
A trust region SQP-filter method for nonlinear second-order cone programming
Computers & Mathematics with Applications
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We present a second order cone programming relaxation with O(n2) variables for quadratic assignment problems, which provides a lower bound not less than the well-known quadratic programming bound. It is further strengthened by additional linear inequalities.