since the emergence of power market, the target of power generating utilities has mainly switched from cost minimization to revenue maximization. they dispatch their power energy generation units in the uncertain environment of power market. as a result, multi-stage stochastic programming has been applied widely by many power generating agents as a suitable tool for dealing with self-scheduling...

background operating room (or) planning involves the creation of a “master surgical schedule” in which surgeons are assigned to specific operating rooms (ors) on specific days of a week. the master schedule is typically one or two weeks long repeatable for several months. objectives the purpose of this study was to recommend using a mathematical program to generate a rotation in a way that the ...

In this paper, a novel framework is proposed to study impacts of regulatory incentive on distributed generation (DG) investment in sub-transmission substations, as well as upgrading of upstream transmission substations. Both conventional and wind power technologies are considered here. Investment incentives are fuel cost, firm contracts, capacity payment and investment subsidy relating to wind ...

abstract it is the purpose of this article to introduce a linear approximation technique for solving a fractional chance constrained programming (cc) problem. for this purpose, a fuzzy goal programming model of the equivalent deterministic form of the fractional chance constrained programming is provided and then the process of defuzzification and linearization of the problem is started. a samp...

We investigate in this paper submodular value functions using complex dynamic programming. In complex dynamic programming (dp) we consider concatenations and linear combinations of standard dp operators, as well as combinations of maximizations and minimizations. These value functions have many applications and interpretations, both in stochastic control (and stochastic zero-sum games) as well ...

The analysis of partially observed stochastic control problems often replaces the unknown state process with its conditional distribution given the observations. This technique rewrites the dynamics in terms of knowable processes whose costs coincide with the original processes. This paper considers stochastic processes having singular behavior and presents an approach which separates the deter...

A wide class of single-product, dynamic inventory problems with convex cost functions and a finite horizon is investigated as a stochastic programming problem. When demands have finite discrete distribution functions, we show that the problem can be substantially reduced in size to a linear program with upper-bounded variables. Moreover,, we show that the reduced problem has a network represent...

In this paper, we review some fuzzy linear programming methods and techniques from a practical point of view. In the rst part, the general history and the approach of fuzzy mathematical programming are introduced. Using a numerical example, some models of fuzzy linear programming are described. In the second part of the paper, fuzzy mathematical programming approaches are compared to stochastic...

fuzzy linear programming problem occur in many elds such as mathematical modeling, control theory and management sciences, etc. in this paper we focus on a kind of linear programming with fuzzy numbers and variables namely fully fuzzy linear programming (fflp) problem, in which the constraints are in inequality forms. then a new method is proposed to ne the fuzzy solution for solving (fflp). ...

In this paper, we propose a stochastic programming model, which considers a ratio of two nonlinear functions and probabilistic constraints. In the former, only expected model has been proposed without caring variability in the model. On the other hand, in the variance model, the variability played a vital role without concerning its counterpart, namely, the expected model. Further, the expected...