The Economic Dispatch Problem (EDP) is one of the important optimization problem in a power system. Traditionally, in EDP, the cost function for each generator has been approximately represented by a single quadratic function. The main aim of EDP is to minimize the total cost of generating real power while satisfying the equality constraints of power balance and the inequality generator capacit...

The problem of estimating the thickness and the optical constants of thin films using transmission data only is very challenging from the mathematical point of view, and has a technological and an economic importance. In many cases it represents a very ill-conditioned inverse problem with many local-nonglobal solutions. In a recent publication we proposed nonlinear programming models for solvin...

( Global optimization is an essential part of any kind of system. Various algorithms have been proposed that try to imitate the learning and problem solving abilities of the nature up to certain level. The main idea of all nature-inspired algorithms is to generate an interconnected network of individuals, a population. Although most of unconstrained optimization problems can be easily handled w...

The satisfiability (SAT) problem is a fundamental problem in mathematical logic, inference, automated reasoning, VLSI engineering, and computing theory. In this paper, following CNF and D N F local search methods, we introduce the Universal SAT problem model, UniSAT, which transforms the discrete SAT problem on Boolean space (0, l}"' into an unconstrained global optimization problem on real spa...

In this paper, we apply Sequential Unconstrained Minimization Techniques (SUMTs) to the classical formulations of both the classical L1 norm SVM and the least squares SVM. We show that each can be solved as a sequence of unconstrained optimization problems with only box constraints. We propose relaxed SVM and relaxed LSSVM formulations that correspond to a single problem in the corresponding up...

Genetic Algorithms (GAs) have been successful in global optimization problems, optimal control, pattern recognition, resource allocation and others. The use of GAs was introduced for the optimal control of discrete time system. After transforming optimal control problem into unconstrained optimization one with respect to control variables, we utilized GAs to solve this optimization problem, and...

Direct use of denoising and mesh reconstruction algorithms on point clouds originating from multi-view images is often oblivious to the reprojection error. This can be a severe limitation in applications which require accurate point tracking, e.g., metrology. In this paper, we propose a method for improving the quality of such data without forfeiting the original matches. We formulate the probl...

This paper presents novel algorithms that iteratively converge to a local minimum of a real-valued function ( ) subject to the constraint that the columns of the complex-valued matrix are mutually orthogonal and have unit norm. The algorithms are derived by reformulating the constrained optimization problem as an unconstrained one on a suitable manifold. This significantly reduces the dimension...