The primary mission of the
Stochastic Modeling, Analysis and Control (SMAC) Laboratory, co-directed by
Drs. Jeffrey Kharoufeh and Lisa Maillart, is to support doctoral-level research that
addresses the mathematical modeling, analysis and control of engineering, service
and other systems that have inherently stochastic elements. Research in the lab emphasizes analytical and
computer-based modeling of such systems (e.g., energy, reliability, maintenance,
production, telecommunications, inventory, medical decision making, healthcare
operations, healthcare policy), and their optimization by exploiting applied
probability, stochastic processes and stochastic optimal control techniques
(e.g., completely and partially observed Markov decision processes).
This collaborative laboratory’s aim
is to generate, analyze and provide viable solutions to complex, often
sequential, decision-making problems in uncertain environments. The SMAC Lab is primarily funded through grants
from the National Science Foundation, the U.S. Department of Defense, the U.S. Department
of Veterans Affairs and other governmental agencies. Current research thrusts in the laboratory
include:
- the modeling,
analysis and optimization of energy storage systems;
- maintenance
optimization of wind energy systems;
- degradation-based
reliability modeling and evaluation;
- data-driven,
adaptive maintenance planning models;
- spare
parts inventory modeling and control;
- dynamic
optimal control of service systems;
- co-sourcing
and pricing in customer contact centers;
- medical
decision making applications in organ transplantation,
- cardiac
device care and therapy sequencing;
- healthcare
operations applications in vaccine administration and donor milk
processing;
- health
policy applications in organ allocation and paid sick days legislation.