2016 INFORMS Annual Meeting Program

362 / 561

INFORMS Nashville – 2016
362
TD89
Broadway C-Omni
Modeling Information for Intelligent Transportation
Systems
Sponsored: TSL, Intelligent Transportation Systems (ITS)
Sponsored Session
Chair: Lili Du, Illinois Institute of Technology, 3201 South Dearborn
Street, Chicago, IL, 60616, United States,
1 - Information Spreading Dynamics Over Vehicular Ad Hoc Network
On Road Segments Based On Cell Transmission Model
Siyuan Song, Illinois Institute of Technology, Department of Civil,
Architectural, and Environmental Engineering, Chicago, IL, 60616,
United States, , Lili Du, Xiang-Yang Li
This research develops an information-traffic coupled cell transmission model (IT-
CTM) to capture discrete information spreading dynamics along with traffic flow
dynamics on a road segment. The IT-CTM is built upon CTM, and involves
mathematical formulations to capture in-cell and intro-cell information spreading
so that we can track the information spreading dynamics along the chain of IT-
CTM cells. Numerical experiments based on simulation data were conducted to
validate the accuracy of the proposed approach.
2 - How Likely Am I To Find Parking? – Modeling of Stochastic
Parking Processes And Probabilistic Estimation Of Parking
Availability
Jun Xiao, Arizona State University, Tempe, AZ, United States,
, Yingyan Luo, Joshua Frisby
This research has developed two Markov models to describe the stochastic
parking process with capacity constraint. Given parameters in the process, the
Markov transition matrix can be calculated for each model, which in turn leads to
the probability distribution of the parking facility occupancy as a function of time.
Mathematical properties of these models have been derived analytically under
specific conditions. Using real data from San Francisco, we have demonstrated
that the proposed approach is able to predict time-dependent occupancy
accurately.
3 - Identifying Social Interaction Networks For Planned
Special Events
Arif Mohaimin Sadri, Purdue University, West Lafayette, IN,
United States, , Samiul Hasan, Satish Ukkusuri,
Juan Esteban Suarez
Planned Special Events (PSE) include large sporting events, conventions and
other similar events. Because of specific locations and times of occurrence, PSEs
are associated with operational needs that can be anticipated and managed ahead
of time. Social media platforms can be used to disseminate information more
efficiently. In this study, we propose a new technique to infer social interaction
networks for PSEs by using data from Twitter. This network of direct social
influence can serve as an important tool to disseminate information effectively
and manage real-time traffic.
4 - Psychological Effects Of Real-Time TravelInformation On Route
Choice Behavior Of Heterogeneous Travelers – Analysis Of
Interactive Driving Simulator Experiment Data
Dong Yoon Song, Purdue University, School of Civil Engineering,
West Lafayette, IN, United States, ,
Srinivas Peeta
Using interactive driving simulator data, we investigate the psychological effects
of real-time travel information on route choice decision-making by considering
travelers’ heterogeneity in information perception. An analytical framework for
characterizing the traveler classes and interpreting the psychological processes
under the information provision for each class is proposed.
TD90
Broadway D-Omni
Health Care, Modeling XI
Contributed Session
Chair: Miao Bai, Lehigh University, Bethlehem, PA, 18015,
United States,
1 - Evaluating Prioritization Schemes For Hepatitis C Treatment
Under Budget Constraints
Lauren E Cipriano, Assistant Professor, Ivey Business School,
1255 Western Road, Room 2361, London, ON, N6G 0N1, Canada,
, Shan Liu, Kaspar S. Shazada,
Mark Holodniy, Jeremy D Goldhaber-Fiebert
Highly effective, but expensive, treatments could improve the health of
individuals chronically infected with hepatitis C virus (HCV). We develop a multi-
period HCV treatment budget allocation model to evaluate the trade-offs of
prioritization schemes including first-come first-served, priority to patients with
most severe disease, and priority to patients based on incremental cost
effectiveness ratio. We also apply an optimization framework to determine the
priority sequence that maximizes net monetary benefit in the population. Explicit
prioritization guidelines targeting younger patients with more severe disease first
provide the greatest population health benefits.
2 - Robust Surgery Planning And Scheduling With Downstream Bed
Capacity In ICU
Chun Peng, PhD Candidate, Beijing Institute of Technology,
Haidian District, 5 South Street, Beijing, 100081, China,
, Jinlin Li, Shanahan Wang
Due to the coupled effect of multiple sources of uncertainty, planning and
scheduling surgeries is a complicated combinatorial optimization problem. In this
paper, we consider the downstream bed capacity in ICU, employ uncertainty set
to capture the uncertainties for surgery duration and length-of-stay in ICU. Then,
we propose a two stage robust model to address these uncertainties, derive the
tractable robust counterpart. Numerical results show that, compared with
uncertainty of length-of-stay, surgery duration uncertainty has a significant effect
on the total cost and the overtime of blocks, whereas uncertainty of length-of-
stay has a dramatic impact on the amount of short beds in ICU.
4 - Using Simulation To Improve Access To Care For
Underserved Populations
Rozhin Doroudi, Northeastern University, 360 Huntington Ave,
Boston, MA, 02115, United States,
Ayten Turkcan, Tammy Toscos, Huanmei Wu, Brad Doebbeling
Underserved patients experience multiple barriers for health care access.
Community Health Centers play an important role in improving access to care for
the underserved by accepting all patients regardless of their financial status. We
developed simulation models tailored for three different CHCs from a range of
geographic and populations with various clinical operational concerns. We tested
several scenarios and found best interventions to enhance patient access to care.
5 - Reactive Surgery Rescheduling On The Day Of Surgery
Miao Bai, Lehigh University, Bethlehem, PA, 18015, United States,
, R.H. Storer, G.L. Tonkay, Terrill Theman
Surgery schedules are subject to disruptions on the day of surgery due to random
surgical durations, insufficient resource, unpunctual patients and emergency. We
incorporate a sample-based gradient descent algorithm in a rescheduling strategy
to make timely adjustment to alleviate the negative consequences of schedule
disruptions. Our objective is to minimize the cost of patient waiting time, surgeon
idle time, operating room (OR) blocking time, OR overtime and post-anesthesia
care unit (PACU) overtime in multiple OR with PACU capacity constraints.
Numerical results demonstrate the effectiveness of our method in reducing the
overall cost on the day of surgery.
TD94
5th Avenue Lobby-MCC
Technology Tutorial: FICO
Technology Tutorial
1 - FICO: How To Deploy Your Analytic Models To Empower Non-
technical Business Users
James Williams, FICO, Roseville, MN, United States,
You have a team with great analytics background. They have developed advanced
analytical tools using SAS, Python, R or with your current traditional
optimization solver. They have derived crucial insights from your data, and
figured out how your decisions shape your customers’ behaviors. Now it’s time to
put these critical analytical insights in the hands of your non-technical business
users. In this tutorial, we will cover how FICO’s Optimization Suite (including
Xpress and Optimization Modeler) make it possible to embed your analytic
models in user-friendly business-user facing applications. Learn how you can
supercharge your analytic models with simulation, optimization, reporting, what-
if analysis and agile extensibility.
TD89