The determination of ordered weighted averaging (OWA) operator weights is a very important issue of applying the OWA operator for decision making. One of the first approaches, suggested by O’Hagan, determines a special class of OWA operators having maximal entropy of the OWA weights for a given level of orness; algorithmically it is based on the solution of a constrained optimization problem. I...

The singular function boundary integral method is applied for the solution of a Laplace equation problem over an L-shaped domain. The solution is approximated by the leading terms of the local asymptotic solution expansion, while the Dirichlet boundary conditions are weakly enforced by means of Lagrange multipliers. Estimates of great accuracy are obtained for the leading singular coe:cients, a...

This paper presents a transmission-constrained unit commitment method using a Lagrangian relaxation approach. Based on a DC power flow model, the transmission constraints are formulated as linear constraints. The transmission constraints, as well as the demand and spinning reserve constraints, are relaxed by attaching Lagrange multipliers. A three-phase algorithmic scheme is devised including d...

Recursive matrix relations for kinematics and dynamics of a spatial three-degrees-of-freedom 3-RPS parallel mechanism are established in this paper. Three identical legs connect the moving platform by revolute joints. Knowing the motion of the platform, we develop first the inverse kinematical problem and determine the positions, velocities and accelerations of the robot. Further, the inverse d...

This paper presents a problem-independent framework that uni es various mechanisms for solving discrete constrained nonlinear programming (NLP) problems whose functions are not necessarily di erentiable and continuous. The framework is based on the rst-order necessary and su cient conditions in the theory of discrete constrained optimization using Lagrange multipliers. It implements the search ...

We consider robust stochastic optimization problems for risk-averse decision makers, where there is ambiguity about both the decision maker's risk preferences and the underlying probability distribution. We propose and analyze a robust optimization problem that accounts for both types of ambiguity. First, we derive a duality theory for this problem class and identify random utility functions as...

We introduce and study the primal-dual exterior point (PDEP) method for convex optimization problems. The PDEP is based on the Nonlinear Rescaling (NR) multipliers method with dynamic scaling parameters update. The NR method at each step alternates finding the unconstrained minimizer of the Lagrangian for the equivalent problem with both Lagrange multipliers and scaling parameters vectors updat...

Recently a new blind equalization method was proposed for the 16QAM constellation input inspired by the maximum entropy density approximation technique with improved equalization performance compared to the maximum entropy approach, Godard's algorithm, and others. In addition, an approximated expression for the minimum mean square error (MSE) was obtained. The idea was to find those Lagrange mu...

Interference and collisions greatly limit the throughput of mesh networks that used contention-based MAC protocols such as 802.11. It is widely believed that significantly higher throughput is achievable if transmissions are scheduled. However, since the typical approach to this throughput optimization requires optimizing over a space that is exponential in the number of links, the optimal thro...

A ctitious domain method based on boundary Lagrange multipliers is proposed for linear elasticity problems in two dimensional domains. The solution of arising saddle-point problem is obtained iteratively using MINRES method with a positive deenite block diagonal preconditioner which is based on a fast direct solver for diiusion problems. Numerical experiments demonstrate the behavior of conside...