Many supply chain problems involve optimization of various conflicting objectives. This paper formulates a green supply chain network throughout a two-stage mixed integer linear problem with uncertain demand and stochastic environmental respects level. The first objective function of the proposed model considers minimization of supply chain costs while the second objective function minimizes CO...

Neural network dynamics are governed by the interaction of spiking neurons. Stochastic aspects of single-neuron dynamics propagate up to the network level and shape the dynamical and informational properties of the population. Mean-field models of population activity disregard the finite-size stochastic fluctuations of network dynamics and thus offer a deterministic description of the system. H...

The concept of picture archiving and communication systems (PACS) is now widely accepted in the medical community. In order to bring the concept to reality, however, innovative designs and implementations are needed. One such design is a ber optic star based PACS. This PACS network is based on a multiplexed passive star local area network with wavelength-division multiplexing to provide separat...

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 accordance wit...

This paper proposes a formal concept of stochastic workflow activity-to-performer affiliation network model. The proposed model is based upon the conceptual formalism of an extended information control net [20] that is revised from the original so as to adopt the probability theory to the activity-to-performer bindings in specifying a workflow procedure. In general, when a workflow management e...

This dissertation develops approaches to rapidly detect malicious network traffic including packets sent by portscanners and network worms. The main hypothesis is that stochastic models capturing a host’s particular connection-level behavior provide a good foundation for identifying malicious network activity in real-time. Using the models, the dissertation shows that a detection problem can be...

Over the last decade we have witnessed the rapid proliferation of online networks and Internet activity. Such activity is considered as a blessing but it brings with it a large increase in risk of computer malware — malignant software that actively spreads from one computer to another. To date, the majority of existing models of malware spread use stochastic behavior, when the set of neighbors ...

There are different techniques for modeling and analysis of communication systems and networks. Because of their critical applications, today’s communication systems should be engineered to rigorous standards and methods. These methods depend on the use of mathematical techniques, and computer aided tools and methodologies. Petri nets (PNs) and their extensions are formalisms for modeling and a...

Stochastic extensions to Petri nets have gained widespread acceptance as a method for describing the dynamic behavior of discrete-event systems. Both simulation and analytic methods have been proposed to solve such models. This paper describes a set of e cient procedures for simulating models that are represented as stochastic activity networks (SANs, a variant of stochastic Petri nets) and com...