In this paper, a delayed Lagrangian network is presented for solving quadratic programming problems. Based on some known results, the delay interval is determined to guarantee the asymptotic stability of the delayed neural network at the optimal solution. One simulation example is provided to show the effectiveness of the approach.

In this paper, we discuss the solution of linear and quadratic eigenvalue complementarity problems (EiCPs) using an enumerative algorithm of the type introduced by Júdice et al. [1]. Procedures for computing the interval that contains all the eigenvalues of the linear EiCP are first presented. A nonlinear programming (NLP) model for the quadratic EiCP is formulated next, and a necessary and suf...

Most research on bilevel linear programming problem  is focused on its deterministic form, in which the coefficients and decision variables in the objective functions and constraints are assumed to be crisp. In fact, due to inaccurate information, it is difficult to know exactly values of coefficients that used to construct a bilevel model. The interval set theory is suitable for describing and...