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: a sudden jump in blood demand during natural disasters may have strong negative impact on the performance of blood supply chain. appropriate response to the emergency situations, requires predictive approach to determining the optimal allocation of blood supply chain resources for various disaster scenarios. the present study, thus, presents an optimization model aime...

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 paper proposes a stochastic framework for demand response (dr) aggregator to procure dr from customers and sell it to purchasers in the wholesale electricity market. the aggregator assigns fixed dr contracts with customers based on three different load reduction strategies. in the presented problem the uncertainty of market price is considered and the risk of aggregator participation is ma...

The present paper addresses an effective cyber defense model by applying information fusion based game theoretical approaches‎. ‎In the present paper, we are trying to improve previous models by applying stochastic optimal control and robust optimization techniques‎. ‎Jump processes are applied to model different and complex situations in cyber games‎. ‎Applying jump processes we propose some m...

in this work an improved method for designing a linear vibrational absorber, excited by random vibrations is presented and analyzed. first, analytical expressions, for non-stationary white noise accelerations, are derived. the criterion is different from the conventional criteria, used for structural design under random vibration, and it is based on minimum displacement or acceleration response...

in this study, we considered an inflationary inventory control model under non-deterministic conditions. we assumed the inflation rate as a normal distribution, with any arbitrary probability density function (pdf). the objective function was to minimize the total discount cost of the inventory system. we used two methods to solve this problem. one was the classic numerical approach which turne...

this work presents a hybrid method for motif discovery in dna sequences. the proposed method called spso-lk, borrows the concept of chebyshev polynomials and uses the stochastic local search to improve the performance of the basic pso algorithm as a motif finder. the chebyshev polynomial concept encourages us to use a linear combination of previously discovered velocities beyond that proposed b...

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...