Abstract
We consider the problem of finding the global minimum of the least squares Stress function with L1 distances in multidimensional scaling. The problem can be formulated as a quadratic programming problem with complementarity constraints and solved as a two level optimization problem with combinatorial minimization at the upper level and convex quadratic programming at the lower level. In this paper, we propose a parallel branch and bound algorithm for this two level optimization problem.
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