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Title: Modeling of Air Traffic Over the North Atlantic Airspace This
research deals with a comprehensive study of the air traffic over
the North Atlantic (NAT) Ocean. The main purpose of
the study is to assess the fuel savings benefit of proposed changes
to the separation standards in the NAT Minimum Navigation Performance
Specification (MNPS) airspace. Using the separation standards
from the 1996 NAT system as the baseline, this research investigates
four different separation scenarios: Reduced Vertical Separation
Minima, Reduced Vertical and Longitudinal Separation Minima, Reduced
Vertical and Horizontal Separation Minima, and Free Flight. A
fast time simulation model is used to investigate the effect of
the separation scenarios on several measures of system performance
such as fuel consumption and communication loadings. Title: Intelligent Transportation Systems Information
technology is yielding existing solutions to such transpprtation
problems as congestion, safety, and pollution. ISE faculty, in collaboration
with the Rutgers Center for Infrastructure and Transportation, are
developing real-time monitoring and control solutions to manage
traffic efficiently during disruptive occurrences such as construction
activity or accidents. Title: Two-Person Zero-Sum Communication Stochastic Games Two-person
zero-sum communication stochastic games with finite state and action
spaces are considered under the long-run average payoff criterion.
On a restricted set of stationary strategies where every pair of
actions is taken with a positive probability, a communicating stochastic
game is irreducible. In order to solve a communication stochastic
game by making use of the communication property, Hoffman and Karp's
algorithm is applied successively over a sequence of restricted
strategy spaces that gets larger until an E - optimal stationary
strategy pair is obtained for any E > 0. Two equivalent algorithms
are presented. Convergence issues are discussed under different
ergodic structures of communicating stochastic games. Convergence
of the proposed algorithm is proven for communicating stochastic
games that have optimal stationary strategies with a value independent
of the initial state. Examples are given to demonstrate convergence
of the proposed algorithm when the specified conditions hold and
a case where this algorithm does not work. Title: A Decomposition Approach for Undiscounted Two-Person Zero-Sum Stochastic Games Two
person zero-sum stochastic games are considered under the iong-run
avearage expected payoff criterion. State and action spaces are
assumed finite. By making of the concept of maximal communicating
classes, the following decomposition algorithm is introduced for
solving two-person zero-sum stochastic games: First, the state space
id decomposed into maximal communicating classes. Then, these classes
are organized in an hierarchical order where each level may contain
more than one maximal communicating class. Best stationary strategies
for the states in a maximal communication class at a level are determined
by using the best stationary strategies of the states in the previous
levels that are accessible from that class. At the initial level,
a restricted game is defined for each closed maximal communicating
class and these restricted games are solved independently. It is
shown that the proposed decomposition algorithm is exact in the
sense that the solution obtained from the decomposition procedure
gives the best stationary strategies for the original stochastic
game. Title: Substitutable Product Inventory Control Substitutable product inventory problem is analyzed using the
concepts of
stochastic game theory. It is assumed that there are two substitutable
products that are sold by different retailers and the demand for each product
is random. Game theoretic nature of this problem is the result of
substitution between products. Since retailers compete for the substitutable
demand, ordering decision of each retailer depends on the ordering decision
of the other retailer. Under the discounted payoff criterion, this problem
is formulated as a two-person nonzero-sum stochastic game. In the case of
linear ordering cost, it is shown that there exists a Nash equilibrium
characterized by a pair of stationary base stock strategies for the infinite
horizon problem. This is the unique Nash equilibrium within the class of
stationary base stock strategies. Title: Integrating PID Controllers into SPC Applications: Tuning, Monitoring, and Performance Analysis In this
research, we develop a technique for integrating PID controllers into the
quality control system. We consider pure-gain and first-order processes subject
to white noise disturbances and random mean shifts. Our aim is to demonstrate
that performance improvements could be achieved using off-the-shelf controllers.
We derive an expression for the sensitivity of a minimum variance (MV) control
system and use this result to demonstrate that a stationary system may become
extremely sensitive when mean shifts are present. Experimental design
techniques are used to demonstrate that a "sub-optimal" PID control may be
implemented without producing a large negative impact on the system.
Furthermore, these results are used to develop formulas for selecting the
controller parameters as well as acceptable ranges for these parameters. The
addition of PID control requires modification of the statistical process
monitoring scheme. We explore this and make recommendations for choosing the
best statistic. Cost models are introduced to assist in the evaluation of the
relative advantages of each of the proposed control schemes. Title: A Generalized Forecasting Model for Predicting the Performance of Repair Stations The
objective of this research is to develop a generalized mathematical
model using the modified nonhomogeneous Poisson process to (1) evaluate
the performance of the repair stations, (2) identify significant
covariate factors that contribute to the unfavorable rating, and
(3) obtain guidelines which can be used to prioritize inspection
activities. A distinguish feature of this general model is that
it combines the two mutually dependent stochastic processes, one
for monitoring the subsystem performance and the other for modeling
the inspection visits, as the subsystem performance and the inspection
visits are related. Title: Investigating Dynamic Threshold Weighted Voting Systems In
many applications, ranging from target detection to safety monitoring
protection systems, a decision has to make on whether or not to
accept the hypothesis based on the given information so that the
probability of making a correct decision is maximized. This research
focuses on the threshold weighted voting systems and develops a
general methodology to evaluate the dependability of dynamic threshold
weighted voting systems. A general recursive dependability time-dependent
function of the systems is also investigated. Title: Designing Client-Server Type Transaction Processing Systems This
research focuses on designing and analyzing the performance of client-server
systems in transaction processing environments. Transactions
bring the workload from clients and the requested services are carried
out by the servers. Our research involves detailed analysis
of the underlying queueing network of clients, communication networks
involved, server nodes with their disks and databases. We
pursue both analytical and simulation approaches to obtain response
times and other performance measures as well as to study design
issues such as work load allocation Title: Correlation Analysis of Manufacturing Systems The
purpose of this research is to study the performance effects of
correlations (as proxies of temporal dependence) in manufacturing
systems. The project will identify random components of manufacturing
systems with appreciable correlations; will study their impact on
performance statistics; and will develop modeling technologies to
capture correlations whenever present in appreciable magnitudes.
Potential random components include stochastic processes of
customer demands, order lead times, machine failures, and down times.
The project will employ a novel modeling methodology, called
TES/QTES, which emphasizes explicit modeling of correlations in
such stochastic processes. It will further be used to explore
the impact of correlations on various manufacturing performance
measures and optimal operating policies. Title: Development of Analytical Methods for Aviation Safety Risk Modeling, Assessment, and Management This research presents a plan to develop/adapt analytical methods for aviation risk modeling, assessment, and management and to provide analytical support to the Federal Aviation Administration's Risk Management Decision Support (RMDS) Research & Development Project. The research is decomposed into four major focal areas. These are a) Risk Identification & Measurement, b) Risk Modeling, c) Risk Assessment, and d) Risk Management. The three-year research plan includes, among others, an investigation of multivariate statistical techniques for performance measure reduction, causal analysis of aircraft accidents using a new Aviation System Risk Model (ASRM), organizational risk profiling, uncertainty analysis, and multiobjective risk management. The models developed during the course of the proposed research will be integrated into a new proof-of-concept web-based software prototype, the Aviation Risk Analysis and Management (AvRAM) System.
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