The interconnection of modern electric power systems allows utilities to obtain significant savings in operational cost by scheduling power purchases. In a deregulated environment, utilities have only partial knowledge of the price of power available in the market. This paper presents a solution to the optimal power purchase problem in a utility by considering ellipsoidal cost coefficient uncer...

It is well-established that equity returns are not Normally distributed, but what should the portfolio manager do about this, and is it worth the effort? It is now feasible to employ better multivariate distribution families that capture heavy tails and skewness in the data; we argue that among the best are the Student t and skewed t distributions. These can be efficiently fitted to data, and s...

It is well-established that equity returns are not Normally distributed, but what should the portfolio manager do about this, and is it worth the effort? As we describe, there are now some good choices for multivariate modeling distributions that capture heavy tails and skewness in the data; we argue that among the best are the (Student) t and skewed t distributions. These can be efficiently ca...

In the literature two approaches of productivity analyses can be found, namely the neoclassical approach and the frontier approach. Neoclassical analysis weights inputs by value shares, a procedure that requires data on factor input shares or prices. This approach imputes productivity growth to factors, but cannot distinguish a movement towards the efficiency frontier and a movement of the latt...

In this article, we investigate the measurement of performance in DMUs in which input and/or output values are given as imprecise data. By imprecise data, we mean that in some cases, we only know that the actual values are inside certain intervals, and in other cases, data are specified only as ordinal preference information. In this article, we present two distinct perspectives for determining...

in this paper imprecise target models has been proposed to investigate the relation between imprecise data envelopment analysis (idea) and mini-max reference point formulations. through these models, the decision makers' preferences are involved in interactive trade-off analysis procedures in multiple objective linear programming with imprecise data. in addition, the gradient projection type me...

Data envelopment analysis (DEA) is a mathematical programming technique for identifying efficiency scores of decision making units (DMUs). Since DEA models cannot present efficient frontiers of PPS, in order to do this, we introduce a method for identifying efficient frontier for DMUs with interval data.

We investigate a continuous-time mean–variance portfolio selection problem. Different from the general stochastic dynamic programming approach, such as using Hamilton–Jacobi–Bellman (HJB) equation, this paper adopts the Lagrange duality method and the finite difference approach to derive explicit closed-form expressions for the efficient investment strategy and the mean–variance efficient front...