dynamic economic load dispatch is one of the most important roles of power generation’s operation and control. it determines the optimal controls of production of generator units with predicted load demand over a certain period of time. economic dispatch at minimum production cost is one of the most important subjects in the power network’s operation, which is a complicated nonlinear constraine...

according to this fact that wind is now a part of global energy portfolio and due to unreliable and discontinuous production of wind energy; prediction of wind power value is proposed as a main necessity. in recent years, various methods have been proposed for wind power prediction. in this paper the prediction structure involves feature selection and use of artificial neural network (ann). in ...

the multiple traveling salesman problem (mtsp) is a generalization of the famous traveling salesman problem (tsp), where more than one salesman is used in the solution. although the mtsp is a typical kind of computationally complex combinatorial optimization problem, it can be extended to a wide variety of routing problems. this paper presents an efficient and evolutionary optimization algorith...

the aim of this study was to estimate suspended sediment by the ann model, dt with cart algorithm and different types of src, in ten stations from the lorestan province of iran. the results showed that the accuracy of ann with levenberg-marquardt back propagation algorithm is more than the two other models, especially in high discharges. comparison of different intervals in models showed that r...

the dynamic facility layout problem (dflp) is the problem of finding positions of departments onthe plant floor for multiple periods (material flows between departments change during the planning horizon)such that departments do not overlap, and the sum of the material handling and rearrangement costs isminimized. in this paper a new optimization algorithm inspired from colonizing weeds, invasi...

one of the most important measures needed to be done in times of crisis is to optimize the allocation and distribution of resources among individuals. time is a critical factor effective to increase the number of people rescued by the relief activities.in this paper, we present a relief vehicle routing model in the affected area which uses covering tour approach to reduce total response time. a...

this paper presents a probabilistic optimal power flow (popf) algorithm considering different uncertainties in a smart grid. different uncertainties such as variation of nodal load, change in system configuration, measuring errors, forecasting errors, and etc. can be considered in the proposed algorithm. by increasing the penetration of the renewable energies in power systems, it is more essent...

in this paper, a block-based method in wavelet domain for sar image coding is presented based on the ezbc algorithm. to better preserve edges and textural structure in sar images, instead of using traditional dyadic wavelet transform, a packet wavelet is employed. to improve the efficiency of the ezbc algorithm for sar image coding, a modified version of this algorithm, is proposed. this modifi...

in this paper, tender problems in an automobile company for procuring needed items from potential suppliers have been resolved by the learning algorithm q. in this case the purchaser with respect to proposals received from potential providers, including price and delivery time is proposed; order the needed parts to suppliers assigns. the buyer’s objective is minimizing the procurement costs thr...

the infomax algorithm is a popular method in blind source separation problem. in this article an extension of the infomax algorithm is proposed that is able to separate mixed signals with any sub- or super-gaussian distributions. this ability is the results of using two different nonlinear functions and new coefficients in the learning rule. in this paper we show how we can use the distribution...