Solving Quadratic Assignment Problems Using Convex Quadratic Programming Relaxations
نویسندگان
چکیده
We describe a branch and bound algorithm for the quadratic assignment problem QAP that uses a convex quadratic programming QP relaxation to obtain a bound at each node The QP subproblems are approximately solved using the Frank Wolfe algorithm which in this case requires the solution of a linear assignment problem on each iteration Our branching strategy makes extensive use of dual information associated with the QP subproblems We obtain state of the art computational results on large benchmark QAPs
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