Applications of parametric programming and eigenvalue maximization to the quadratic assignment problem

We investigate new bounding strategies based on different relaxations of the quadratic assignment problem. In particular, we improve the lower bound found by using an eigenvalue decomposition of the quadratic part and by solving a linear program for the linear part. The improvement is accomplished by applying a steepest ascent algorithm to the sum of the two bounds.

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