On Copositive Programming and Standard Quadratic Optimization Problems

摘要: A standard quadratic problem consists of finding global maximizers a form over the simplex. In this paper, usual semidefinite programming relaxation is strengthened by replacing cone positive matrices completely (the which allow factorization FFT where F some non-negative matrix). The dual copositive (i.e., those yield on orthant). This conic formulation allows us to employ primal-dual affine-scaling directions. Furthermore, these approaches are combined with an evolutionary dynamics algorithm generates primal-feasible paths along objective monotonically improved until local solution reached. particular, affine scaling directions used escape from maxima encountered during phase.