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...

background and objectives: operating room (or) scheduling is key to optimal operating room productivity. the significant uncertainty associated with surgery duration renders scheduling of surgical operation a challenging task. this paper proposes a novel computational stochastic model to optimize scheduling of surgeries with uncertain durations. the model considers various surgical operation co...

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...

this article aims at designing the mathematical model for aras dam reservoir in time operation with missions of agriculture needs safeguarding, water electric energy production and torrent controls. reservoir system relations determinate and these relations at framework of are determined and stochastic dynamic programming are calculated executive results of this model are presentation of guides...

In today’s competitive market, those producers who can quickly adapt themselves todiverse demands of customers are successful. Therefore, in order to satisfy these demands of market, Mixed-model assembly line (MMAL) has an increasing growth in industry. A mixed-model assembly line (MMAL) is a type of production line in which varieties of products with common base characteristics are assembled o...

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 d...

Background and Objectives: Operating room (OR) scheduling is key to optimal operating room productivity. The significant uncertainty associated with surgery duration renders scheduling of surgical operation a challenging task. This paper proposes a novel computational stochastic model to optimize scheduling of surgeries with uncertain durations. The model considers various surgical operation co...

The significant penetration rate of wind turbines in power systems made some challenges in the operation of the systems such as large-scale power fluctuations induced by wind farms. Gas-fired plants with fast starting ability and high ramping can better handle natural uncertainties of wind power compared to other traditional plants. Therefore, the integration of electrical and natural gas syste...

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...