A new bound for the quadratic assignment problem based on convex quadratic programming
نویسندگان
چکیده
We describe a new convex quadratic programming bound for the quadratic assignment problem (QAP). The construction of the bound uses a semideenite programming representation of a basic eigenvalue bound for QAP. The new bound dominates the well-known projected eigenvalue bound, and appears to be competitive with existing bounds in the tradeoo between bound quality and computational eeort.
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ورودعنوان ژورنال:
- Math. Program.
دوره 89 شماره
صفحات -
تاریخ انتشار 2001