this paper presents an approach for solving a nonlinear stochastic differential equations (nsdes) using a new basis functions (nbfs). these functions and their operational matrices areused for representing matrix form of the nbfs. with using this method in combination with the collocation method, the nsdes are reduced a stochastic nonlinear system of equations and unknowns. then, the error anal...

In this paper one of the important “end of life options” (remanufacturing) has been analysed. Among the related studies surveyed the various remanufacturing aspects, less attention has been paid to the stochastic process routing. In this regard, a remanufacturing process routing with stochastic activities is modelled as a GERT network. One of the efficient ways to analyse a remanufacturing proc...

The hub location problem arises in a variety of domains such as transportation and telecommunication systems. In many real-world situations, hub facilities are subject to disruption. This paper deals with the multiple allocation hub location problem in the presence of facilities failure. To model the problem, a two-stage stochastic formulation is developed. In the proposed model, the number of ...

Quality of service (QoS) optimization for end-to-end (e2e) services always depends on performance analysis in cloud-based service delivery industry. However, performance analysis of e2e services becomes difficult as the scale and complexity of virtualized computing environments increase. In this paper, the authors present a novel hierarchical stochastic approach to evaluate the QoS of e2e virtu...

Many AI problems can be conveniently encoded as discrete constraint satisfaction problems. It is often the case that not all solutions to a CSP are equally desirable | in general, one is interested in a set of \preferred" solutions (for example, solutions that minimize some cost function). Preferences can be encoded by incorporating \soft" constraints in the problem instance. We show how both h...

In many applications of stochastic programming there is some uncertainty about the probability distribution P of the random parameters. The incomplete knowledge of the probability distribution can be described by assuming that P belongs to a specified class P of probability distributions. This in turn suggests to use the minimax decision rule. The first results were concerned with stochastic li...