2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
208
MC94
5th Avenue Lobby-MCC
Technology Tutorial: GAMS/LINDO
Technology Tutorial
1 - GAMS: Introduction To Modeling In GAMS
Steven P Dirkse, GAMS Development Corporation, Washington,
DC, United States,
We demonstrate many of the capabilities of the GAMS software as we start with a
simple optimization model and build it out by adding nonlinear and integer
variables to the model and connecting it with a GUI in a sample application.
2 - LINDO: Optimization Modeling Made Easy
Mark A Wiley, LINDO Systems Inc, 1415 No Dayton Street,
Chicago, IL, 60622, United States,
Gautier Laude
Monday, 3:10PM - 4:00PM
Monday Plenary
Davidson Ballroom-MCC
Omega Rho – 40th Year Anniversary Panel
Plenary Session
Chair: Graham Rand, Lancaster University, United Kingdom,
Lancaster, LA1 4YX
1 - Omega Rho - 40th Year Anniversary Panel
Graham Rand, Lancaster University, Lancaster, United Kingdom,
After a brief introduction to Omega Rho, International Honor Society for
Operations Research and Management Science, as it celebrates its 40th birthday,
four of its distinguished lecturers will revisit their lectures. All four were in the
first group of INFORMS Fellows, created in 2002
2 - Panelist
John R. Birge, Jerry W. and Carol Lee Levin Professor of Operatio,
University of Chicago, Booth School of Business, Chicago, IL, United
States,
3 - Panelist
John D. Little, Massachusetts Institute of Technology, M.I.T. Sloan
School Of Management, Room E62-534, Cambridge, MA, 02142,
United States,
4 - Panelist
Ralph Keeney, Duke University, San Francisco, CA, United States,
5 - Panelist
Alfred Blumstein, Carnegie Mellon University, Heinz College -
Hamburg Hall, Pittsburgh, PA, United States,
Monday, 4:30PM - 6:00PM
MD01
101A-MCC
Data Mining for State Transition Modeling
Sponsored: Data Mining
Sponsored Session
Chair: Victoria C. P. Chen, The University of Texas at Arlington, Dept. of
Ind., Manuf., & Sys. Engr., Campus Box 19017, Arlington, TX, 76019,
United States,
1 - A High-dimensional State Transition Development Framework For
Deicing Activities At Dallas-fort Worth International Airport
Zirun Zhang, FedEx,
For high-dimensional and complex systems, state transitions can be empirically
represented from data to enable system simulation or optimization. This paper
presents a data-driven framework for state transition development in the context
of deicing/anti-icing activities at Dallas-Fort Worth (D/FW) International Airport.
From study of the framework, the D/FW deicing system is stochastic, finite
horizon and discrete-time, non-stationary, and non-convex with mostly
continuous state variables.
2 - State Transition Modeling For An Interdisciplinary Pain
Management Program
Nilabh Ohol, The University of Texas at Arlington,
We discuss state transition modeling for an adaptive interdisciplinary pain
management program at the University of Texas Southwestern Medical Center at
Dallas. Challenges include data collection and preparation, endogeneity, and
statistical modeling for optimization. Different modeling approaches will be
presented, including linear and piecewise linear regression, piecewise linear
networks, and regression splines models.
3 - Challenges In State Transition Modeling For A System Of Electric
Vehicle Charging Stations
Ying Chen, The University of Texas at Arlington,
In order to supervise the running of plug-in hybrid electric vehicle (PHEV)
charging station intelligently, approximated dynamic programming (ADP)
algorithm is proposed to control this system, which is equipped with a distributed
energy storage system charged by solar power, wind power and electricity from
the power grid. The sampling of state space and state transition model are the
critical parts to build a converged future value function (FVF) in ADP considering
the dimension of state space and multicollinearity issue between state variables.
In PHEV charging station control problem, the objective is to minimize the
operational cost.
4 - Multicollinearity In State Transition Modeling
Victoria C. P. Chen, University of Texas, 701 S. Nedderman Drive,
Arlington, TX, 76019, United States, Bancha
Ariyajunya, Ying Chen, Seoung Bum Kim
Multicollinearity is known to have a negative impact on statistical modeling,
specifically with respect to variance inflation. A state transition modeling
approach based on orthogonalization of the state space is presented. Results are
shown for a ground-level ozone pollution stochastic dynamic program.
MD02
101B-MCC
Panel: Funding Issues at NSF
Invited: NSF
Invited Session
Moderator: Sheldon H Jacobson, University of Illinois, 201 N. Goodwin
Avenue (MC258), Urbana, IL, 61801, United States,
1 - Funding Issues At NSF: Broader Impact Changes
Panelist: Sheldon H Jacobson, University of Illinois,
Discuss outcomes of recent NSF-sponsored workshop on Broader Impact, and its
impact on future funding decisions.
2 - Funding Opportunities At The National Science Foundation
Panelist: Diwakar Gupta, University of Minnesota and National
Science Foundation,
3 - Broader Impact at NSF
Panelist: Sheldon Jacobson, University of Illinois,
MD03
101C-MCC
Daniel H. Wagner Prize Competition III
Award Session
Chair: C. Allen Butler, Daniel H Wagner Associates, Inc., 2 Eaton Street,
Hampton, VA, 23669, United States,
1 - IBM Cognitive Technology Helps Aqualia Reduce Costs And Save
Resources In Wastewater Treatment
Alexander Zadorojniy, IBM Research, IBM Haifa Research Lab,
Haifa, Israel, , Segev Wasserkrug, Sergey Zeltyn,
Vladimir Lipets
This work takes a deep dive into operational management optimization problems
in wastewater treatment plants. We used a constrained Markov Decision Process
as the key optimization framework. Our technology was tested in a one-year pilot
at a plant in Lleida, Spain, operated by Aqualia, the world’s 3rd-largest water
company. The results showed a dramatic 13.5 percent general reduction in the
plant’s electricity consumption, a 14 percent reduction in the amount of
chemicals needed to remove phosphorus from the water, and a 17 percent
reduction in sludge production.
MC94