The explosive growth of wireless applications and high demand for wireless resources have created spectruIIl crisis. Many spectrnm occupancy measurements have shown that most of the allocated spectrum experiences inefficient utilization. Hence radically new approaches arc required for better utilization of spectrum. This has motivated the concept of opportunistic spectrum access in the licensed...

In a recent paper, Birgin, Floudas and Mart́ınez introduced an augmented Lagrangian method for global optimization. In their approach, augmented Lagrangian subproblems are solved using the αBB method and convergence to global minimizers was obtained assuming feasibility of the original problem. In the present research, the algorithm mentioned above will be improved in several crucial aspects. On...

Lindell, Nissim, and Orlandi (ASIACRYPT 2013) studied feasibility and infeasibility of general two-party protocols that hide not only the contents of the inputs of parties, but also some sizes of the inputs and/or the output. In this paper, we extend their results to n-party protocols for n ≥ 2, and prove that it is infeasible to securely compute every function while hiding two or more (input o...

We study the convergence of an iterative projection/reflection algorithm originally proposed for solving what are known as phase retrieval problems in optics. There are two features that frustrate any analysis of iterative methods for solving the phase retrieval problem: nonconvexity and infeasibility. The algorithm that we developed, called Relaxed Averaged Alternating Reflections (RAAR), was ...

The design of pumping stations in a water distribution network determines the investment costs and affects large part operating network. In recent years, it was shown that is possible to use flow optimize both concurrently; however, methodologies proposed literature are not applicable real-sized networks. these cases, space solutions huge, small number feasible exists, each evaluation objective...

All practical MPC implementations should have a means to recover from infeasibility. We propose an algorithm designed for linear state-space MPC which transforms an infeasible MPC optimization problem into a feasible one. The algorithm handles possible prioritizations among the constraints explicitly. Prioritized constraints can be seen as an intuitive and structural way to impose process knowl...

Does a given system of linear equations Ax = b have a nonnegative integer solution? This is a fundamental question in many areas, such as operations research, number theory, and statistics. In terms of optimization, this is called an integer feasibility problem. A generalized integer feasibility problem is to find b such that there does not exist a nonnegative integral solution in the system wi...

We present a sequential quadratic optimization (SQO) algorithm for nonlinear constrained optimization. The method attains all of the strong global and fast local convergence guarantees of classical SQO methods, but has the important additional feature that fast local convergence is guaranteed when the algorithm is employed to solve infeasible instances. A two-phase strategy, carefully construct...

In this paper, we analyze the convergence of Alternating Direction Method of Multipliers (ADMM) on convex quadratic programs (QPs) with linear equality and bound constraints. The ADMM formulation alternates between an equality constrained QP and a projection on the bounds. Under the assumptions of: (i) positive definiteness of the Hessian of the objective projected on the null space of equality...

A self-adaptive fitness formulation is presented for constrained evolutionary optimization. The method has been formulated to ensure that slightly infeasible solutions with a low objective function value remain fit. This is seen as a benefit in solving highly constrained problems that have solutions on one or more of the constraint bounds. In contrast, solutions furthest from the constraint bou...