Various mathematical programming methods are developed in the literature for solving quadratic objective optimization problem. Conventional approaches such as Lambda iteration method, gradient method and quadratic programming method are used to solve the quadratic objective optimization problems. These conventional methods have different drawbacks of their own. In Lambda iteration method, it is...

Numerical approaches are developed for solving large-scale problems of extended linear-quadratic programming that exhibit Lagrangian separability in both primal and dual variables simultaneously. Such problems are kin to large-scale linear complemen-tarity models as derived from applications of variational inequalities, and they arise from general models in multistage stochastic programming and...

Quadratic Programming (QP) is the well-studied problem of maximizing over {−1, 1} values the quadratic form ∑ i6=j aijxixj . QP captures many known combinatorial optimization problems, and assuming the unique games conjecture, semidefinite programming techniques give optimal approximation algorithms. We extend this body of work by initiating the study of Quadratic Programming problems where the...

We propose a class of quadratic optimization problems whose exact optimal objective values can be computed by their completely positive cone programming relaxations. The objective function can be any quadratic form. The constraints of each problem are described in terms of quadratic forms with no linear terms, and all constraints are homogeneous equalities, except one inhomogeneous equality whe...

A recursive quadratic programming (RQP) approach is proposed for multiuser detection in multicarrier code-division multipleaccess (MC-CDMA) systems. In this approach, the combinatorial problem associated with the optimal maximum likelihood (ML) detection is relaxed to a quadratic programming (QP) problem first and then a recursive approach is developed to improve the detection performance. Comp...

In this paper a preprocessing algorithm for binary quadratic programming problems is presented. For some types of binary quadratic programming problems, the algorithm can compute the optimal value for some or all integer variables without approximations in polynomial time. When the optimal multiuser detection problem is formulated as a maximum likelihood problem, a binary quadratic programming ...