期刊名称：Department of Computer and System Sciences Antonio Ruberti Technical Reports
印刷版ISSN：2035-5750
出版年度：2010
卷号：2
期号：12
页码：16
语种：English
出版社：Department of Computer and System Sciences Antonio Ruberti. Sapienza, Università di Roma
摘要：A standard quadratic optimization problem (StQP) consists of nding the largest or smallest value of a (possibly indenite) quadratic form over the standard simplex which is the intersection of a hyperplane with the positive orthant. This NP-hard problem has several immediate real-world applications like the Maximum-Clique Problem, and it also occurs in a natural way as a subproblem in quadratic programming with linear constraints. We propose unconstrained reformulations of StQPs, by using dierent approaches. We test our method on clique problems from the DIMACS challenge.
