Probabilistic or stochastic programming is a framework for modeling optimization problems that involve uncertainty.In this paper, we focus on multi-objective linear programmingproblems in which the coefficients of constraints and the righthand side vector are fuzzy random variables. There are several methodsin the literature that convert this problem to a stochastic or<b...

Dynamic systems in many branches of science and industry are often perturbed by various types of environmental noise. Analysis of this class of models are very popular among researchers. In this paper, we present a method for approximating solution of fractional-order stochastic delay differential equations driven by Brownian motion. The fractional derivatives are considered in the Caputo sense...

‎in this paper, we study some kinds of majorizations on $textbf{m}_{n}$ and their linear or strong linear preservers. also, we find the structure of linear or strong linear preservers which are multiplicative, i.e.  linear or strong linear preservers like $phi $ with the property $phi (ab)=phi (a)phi (b)$ for every $a,bin textbf{m}_{n}$.

in this short review we look at recent advances in schramm-loewner evolution (sle) theory and its application to critical phenomena. the application of sle goes beyond critical systems to other time dependent, scale invariant phenomena such as turbulence, sand-piles and watersheds. through the use of sle, the evolution of conformally invariant paths on the complex plane can be followed; hence a...

a linear programming model has been presented for finding an appropriate planning in order to maximize hotel revenue. in this model, a special planning horizon has been considered that includes several busy days of a year. there are several reservation periods that may start a few months earlier. each period of reservation may have different prices and so result different incomes. hotel custome...

The aim of seismic inversion is mapping all of the subsurface structures from seismic data. Due to the band-limited nature of the seismic data, it is difficult to find a unique solution for seismic inversion. Deterministic methods of seismic inversion are based on try and error techniques and provide a smooth map of elastic properties, while stochastic methods produce high-resolution maps of el...

In this paper, we discuss the usual stochastic&lrm;, &lrm;likelihood ratio, &lrm;dispersive and convex transform order between two parallel systems with independent heterogeneous extended generalized exponential components. &lrm;We also establish the usual stochastic order between series systems from two independent heterogeneous extended generalized exponential samples. &lrm;Finally, &lrm;we f...

Abstract. Wind as a resource of renewable energy has obtained an important share of the energy market already. Therefore simulation and prediction of wind speeds is essential for both, for engineers and energy traders. In this paper we analyze the surface wind speed data from three prototypic locations: coastal region (Rotterdam), undulating forest landscape few 100 m above sea level(Kassel), ...

In this paper, we propose an extended relocation model for warehouses configuration in a supply chain network, in which uncertainty is associated to operational costs, production capacity and demands whereas, existing researches in this area are often restricted to deterministic environments. In real cases, we usually deal with stochastic parameters and this point justifies why the relocation m...