In this paper, a stochastic two-stage model is offered for optimization of the day-ahead scheduling of the microgrid. System uncertainties including dispatchable distributed generation and energy storage contingencies are considered in the stochastic model. For handling uncertainties, Monte Carlo simulation is employed for generation several scenarios and then a reduction method is used to decr...

Stochastic differential equations (SDEs) have been applied by engineers and economists because it can express the behavior of stochastic processes in compact expressions. In this paper, by using Grunwald-Letnikov fractional derivative, the stochastic differential model is improved. Two numerical examples are presented to show efficiency of the proposed model. A numerical optimization approach b...

the stochastic reaction diffusion systems may suffer sudden shocks‎, ‎in order to explain this phenomena‎, ‎we use markovian jumps to model stochastic reaction diffusion systems‎. ‎in this paper‎, ‎we are interested in almost sure exponential stability of stochastic reaction diffusion systems with markovian jumps‎. ‎under some reasonable conditions‎, ‎we show that the trivial solution of stocha...

this paper presents a mathematical model for a flow shop scheduling problem consisting of m machine and n jobs with fuzzy processing times that can be estimated as independent stochastic or fuzzy numbers. in the traditional flow shop scheduling problem, the typical objective is to minimize the makespan). however,, two significant criteria for each schedule in stochastic models are: expectable m...

Performance evaluation of electricity distribution units is an important issue between researchers and regulators. Classic Data Envelopment Analysis models with deterministic data have been used by many authors to measure efficiency of power distribution units in different countries. However, Data Envelopment Analysis with stochastic data are rarely used to measure efficiency of distribution co...

In this current study a generalized super-efficiency model is first proposed for ranking extreme efficient decision making units (DMUs) in stochastic data envelopment analysis (DEA) and then, a deterministic (crisp) equivalent form of the stochastic generalized super-efficiency model is presented. It is shown that this deterministic model can be converted to a quadratic programming model. So fa...

multistage stochastic programming is a key technology for making decisions over time in an uncertain environment. one of the promising areas in which this technology is implementable, is medium term planning of electricity production and trading where decision makers are typically faced with uncertain parameters (such as future demands and market prices) that can be described by stochastic proc...

in this current study a generalized super-efficiency model is first proposed for ranking extreme efficient decision making units (dmus) in stochastic data envelopment analysis (dea) and then, a deterministic (crisp) equivalent form of the stochastic generalized super-efficiency model is presented. it is shown that this deterministic model can be converted to a quadratic programming model. so fa...

  Data envelopment analysis (DEA) is a nonparametric approach to evaluate theefficiency of decision making units (DMU) using mathematical programmingtechniques. Almost, all of the previous researches in stochastic DEA have been usedthe stochastic data when the inputs and outputs are normally distributed. But, thisassumption may not be true in practice. Therefore, using a normal distribution wi...

Supply chain network design in perishable product has become a challenging task due to its short life time, spoilage of product in degradation nature and stochastic market demand. This paper focused on designing and optimizing model for perishable product in stochastic demand, which comprises multiple levels from producer, local collector, wholesaler and retailers. The ultimate goal is to optim...