2016 INFORMS Annual Meeting Program

TD89

INFORMS Nashville – 2016

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, ldu3@iit.edu 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, sgong1@hawk.iit.edu, 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, jun.xiao.1@asu.edu, 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, asadri@purdue.edu, 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, song50@purdue.edu, 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, mib411@lehigh.edu 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, lcipriano@ivey.uwo.ca, 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, pengchun12.18@163.com, 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- Rozhin Doroudi, Northeastern University, 360 Huntington Ave, Boston, MA, 02115, United States, doroudi.r@husky.neu.edu, 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, mib411@lehigh.edu, 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, JWilliams@fico.com 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. stay has a dramatic impact on the amount of short beds in ICU. 4 - Using Simulation To Improve Access To Care For Underserved Populations

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