This paper deals with day-ahead programming under uncertainties in microgrids (MGs). A two-stage stochastic programming with the fixed recourse approach was adopted. The studied MG was considered in the grid-connected mode with the capability of power exchange with the upstream network. Uncertain electricity market prices, unpredictable load demand, and uncertain wind and solar power values, du...

Abstract : In this paper , we apply the stochastic dynamic programming to approximate the mean project completion time in dynamic Markov PERT networks. It is assumed that the activity durations are independent random variables with exponential distributions, but some social and economical problems influence the mean of activity durations. It is also assumed that the social problems evolve in ac...

Finding the location for plans like factories or warehousesfor any organization is an important and strategic decision. Costs oftransportation which are the main part of the price of the goods, is thefunction of the location of these projects. to find the optimum locationof these projects, there have been various methods proposed which areusually defined (not random). In reality and in dealing ...

Stochastic programming is a valuable optimization tool where used when some or all of the design parameters of an optimization problem are defined by stochastic variables rather than by deterministic quantities. Depending on the nature of equations involved in the problem, a stochastic optimization problem is called a stochastic linear or nonlinear programming problem. In this paper,a stochasti...

this study develops a long run optimal pattern for nomadic ranchers of fars province under climate uncertainty by simulating dynamic process of livestock and forage productivity as well as employing dynamic stochastic programming. results indicate that the nomadic representatives do not perform, optimally. despite their attachments to livestock as an asset, and their life dependency on livestoc...

stochastic approach to vehicle routing problem: development and theories abstract in this article, a chance constrained (ccp) formulation of the vehicle routing problem (vrp) is proposed. the reality is that once we convert some special form of probabilistic constraint into their equivalent deterministic form then a nonlinear constraint generates. knowing that reliable computer software for lar...

Multistage stochastic programming deals with operational and planning problems that involve a sequence of decisions over time while responding to an uncertain future. Algorithms designed address multistage linear (MSLP) often rely upon scenario trees represent the underlying process. When this process exhibits stagewise independence, sampling-based techniques, particularly dual dynamic algorith...