A probabilistic method for solving the Monge-Kantorovich mass transport problem on R is introduced. A system of empirical measures of independent particles is built in such a way that it obeys a doubly indexed large deviation principle with an optimal transport cost as its rate function. As a consequence, new approximation results for the optimal cost function and the optimal transport plans ar...

many real water resources optimization problems involve conflicting objectives. in this study, multiobjective genetic algorithm nsga-ii, has been developed for optimization the conjunctive use of surface water and groundwater resources and optimal management of supply and demand of agricultural water. here, optimal allocation of land and water resources to the dominant products in najaf abad pl...

Given a finite family of functions, the goal of model selection aggregation is to construct a procedure that mimics the function from this family that is the closest to an unknown regression function. More precisely, we consider a general regression model with fixed design and measure the distance between functions by the mean squared error at the design points. While procedures based on expone...

An optimal risk sharing problem for agents with utility functionals depending only on the expected value and a deviation measure of an uncertain payoff has been studied. The agents are assumed to have no initial endowments. A set of Pareto-optimal solutions to the problem has been characterized, and a particular solution from the set has been suggested. If an equilibrium exists, the suggested s...

needs of human life from the beginning been an important factor we have been threatened by population growth, food security and human well- men of science and technology with a new plan maintain and improve their food security to make it work. in this investigation, meteorological data have been received from synoptic stations based on daily, monthly, and annually trend from iran meteorological...

optimal reactive power dispatch (orpd) is a multi-variable problem with nonlinear constraints and continuous/discrete decision variables. due to the stochastic behavior of loads, the orpd requires a probabilistic mathematical model. in this paper, monte carlo simulation (mcs) is used for modeling of load uncertainties in the orpd problem. the problem is formulated as a nonlinear constrained mul...

Distributed Generations (DGs) are utilized to supply the active and reactive power in the transmission and distribution systems. These types of power sources have many benefits such as power quality enhancement, voltage deviation reduction, power loss reduction, load shedding reduction, reliability improvement, etc. In order to reach the above benefits, the optimal placement and sizing of DG is...