A New Algorithm for Quadratic Programming with Interval-Valued Bound Constraints

In this paper, we study the interval-valued convex quadratic programming with bound constraints. The membership functions of bound constraints are defined, and through solving two general quadratic programming, we define the membership function of objective function. Based on this, the problem is converted into a multi-objective programming by exploiting these membership functions. Finally, the multi-objective programming is converted into a semi-definite programming (SDP) using Schur complement theorem, which can be solved efficiently by using the existed software for SDP.