A stochastic algorithm for solving the sensor selection problem is presented. The problem arises when many sensors are jointly trying to estimate a process but only a subset of them can take measurements at any time step. The proposed stochastic sensor selection strategy is easy to implement and is computationally tractable. The algorithm is illustrated through simple examples of sensor schedul...

Data envelopment analysis (DEA) is a methodology for measuring the relative efficiency of decision making units (DMUs) which ‎consume the same types of inputs and producing the same types of outputs. Believing that future planning and predicting the ‎efficiency are very important for DMUs, this paper first presents a new dynamic random fuzzy DEA model (DRF-DEA) with ‎common weights (using...

It is shown that a category-theoretic definition of chaotic system applies not only to the Smale horseshoe, a prototypical example, but also to Conway’s “Life.” Symbolic dynamics of the “Dining Philosophers” relational system is computed. A category composed of stochastic matrices is defined and its elementary properties are studied. A categorical variant of symbolic dynamics is applied to a fi...

Probability theory, and its dynamic aspect stochastic process theory, is both a venerable subject, in that its roots go back to the mid-seventeenth century, and a young one, in that its modern formulation happened comparatively recently – well within living memory. The year 2003 marked the seventieth anniversary of Kolmogorov’s Grundbegriffe der Wahrscheinlichkeitsrechnung, usually regarded as ...

I introduce and study dynamic persuasion mechanisms. A principal privately observes the evolution of a stochastic process and sends messages over time to an agent. The agent takes actions in each period based on her beliefs about the state of the process and the principal wishes to influence the agent’s action. I characterize the optimal persuasion mechanism and apply it to some examples.

A crucial challenge in future smart energy grids is the largescale coordination of distributed energy demand and generation. The well-known PowerMatcher is a promising approach that integrates demand and supply flexibility in the operation of the electricity system through dynamic pricing and a hierarchical bidding coordination scheme. However, as the PowerMatcher focuses on short-term coordina...

This paper is focused on survival analysis of electrical components. The main goal of this paper is to develop a method for on-line estimation of the Mean Time To Failure (MTTF) of electrical components under dynamic stress levels. The proposed method models the variations of the stress levels as a stochastic process. Hence, a stochastic failure rate function can be developed for each electrica...

Traffic conditions vary over time, and therefore, traffic behavior should be modeled as a stochastic process. In this study, a probabilistic approach utilizing Autocorrelation is proposed to model the stochastic variation of traffic conditions, and subsequently, predict the traffic conditions. Using autocorrelation of the time series samples of density and flow which are collected from segments...

Finite-dimensional stationary dynamic control systems described by linear stochastic ordinary differential state equations with multiple point delays in control are considered. Using the notation, theorems and methods used for deterministic controllability problems for linear dynamic systems with delays in control as well as necessary and sufficient conditions for various kinds of stochastic re...

In this paper we study scheduling problems of multiclass customers on identical parallel processors. A new type of arrival process, called a Markov Decision Arrival Process, is introduced. This arrival process can be controlled and allows for an indirect dependence on the numbers of customers in the queues. As a special case we show the optimality of LEPT and the μc-rule in the last node of a c...