Linear convergence of a type of iterative sequences in nonconvex quadratic programming

By using error bounds for affine variational inequalities we prove that any iterative sequence generated by the Projection DC (Difference-of-Convex functions) decomposition algorithm in quadratic programming is R-linearly convergent, provided that the original problem has solutions. Our result solves in the affirmative the first part of the conjecture stated by Le Thi, Pham Dinh and Yen in their recent paper [8, p. 489].