Abstract. In this paper we derive by means of the duality theory necessary and sufficient optimality conditions for convex optimization problems having as objective function the composition of a convex function and a linear continuous mapping defined on a separated locally convex space with values in an finitedimensional space. We use the general results for deriving optimality conditions for t...

This paper studies a one-sector optimal growth model with linear utility in which the production function is only required to be increasing and upper semicontinuous. The model also allows for a general form of irreversible investment. We show that every optimal capital path is strictly monotone until it reaches a steady state; further, it either converges to zero, or reaches a positive steady s...

In this paper, an optimization problem with a linear objective function subject to a consistent finite system of fuzzy relation inequalities using the max-product composition is studied. Since its feasible domain is nonconvex, traditional linear programming methods cannot be applied to solve it. We study this problem and capture some special characteristics of its feasible domain and optimal so...

Linear programming problems with fuzzy coefficients in the objective function are considered. Emphasis is on the dependence of the optimal solution from linear perturbations of the membership functions of the objective function coefficients as well as on the computation of a robust solution of the fuzzy linear problem if the membership functions are not surely known.

We examine a multidimensional optimisation problem in the tropical mathematics setting. The problem involves the minimisation of a nonlinear function defined on a finite-dimensional semimodule over an idempotent semifield subject to linear inequality constraints. We start with an overview of known tropical optimisation problems with linear and nonlinear objective functions. A short introduction...

In this paper we propose a variant of the random coordinate descent method for solving linearly constrained convex optimization problems with composite objective functions. If the smooth part of the objective function has Lipschitz continuous gradient, then we prove that our method obtains an ε-optimal solution in O(N/ε) iterations, where N is the number of blocks. For the class of problems wit...

wind power has been widely considered in recent years as an available and a clean renewable energy source. the cost of wind energy production is currently the main issue, and increasing the size of wind turbines can reduce wind energy production costs. hence, megawatt wind turbines are being rapidly developed in recent years. in this paper, an aerodynamic analysis of the nrel 5mw turbine is car...

This paper presents a new method for power systems performance optimization using Electromagnetic Transients Simulation. In this method, an emtp-type program (PSCAD/EMTDC) becomes the inner objective function calculation loop of a non-linear optimization program. The procedure is conducted in a Graphical Environment and with the use of specially designed blocks, allows for the selection of any ...

The importance of linear fractional programming comes from the fact that many real life problems are based on the ratio of physical or economic values (for example cost/time, cost/volume, profit/cost or any other quantities that measure the efficiency of a system) expressed by linear functions. Usually, the coefficients used in mathematical models are subject to errors of measurement or vary wi...