2016 INFORMS Annual Meeting Program

POSTER SESSION

INFORMS Nashville – 2016

TB89 Broadway C-Omni

3 - Agent Based Simulation Of Influenza Spread On A College Campus Stephen Hill, University of North Carolina Wilmington, 601 South College Road, Wilmington, NC, 28403-5611, United States, hills@uncw.edu Agent-based simulation has been shown to be a useful tool for exploration of the dynamics of social interaction. In this work, the spread of influenza in the highly- social and compact community of a university campus is explored. Implications for disease control and intervention are described. TB94 5th Avenue Lobby-MCC Technology Tutorial: SAS/SAS-JMP Technology Tutorial 1 - SAS: Building And Solving Optimization Models With SAS SAS provides a broad and deep array of data and analytic capabilities, including data integration, statistics, data and text mining, econometrics and forecasting, and operations research. The SAS optimization, simulation, and scheduling features coordinate easily and fully with other SAS strengths in data handling, analytics, and reporting. OPTMODEL from SAS provides a powerful and intuitive algebraic optimization modeling language and unified support for building and solving LP, MILP, QP, NLP, CLP, and network-oriented models. And because OPTMODEL is also a SAS procedure (software module), it integrates seamlessly with the entire family of SAS functions, procedures, and macros. We’ll demonstrate how you can use OPTMODEL to solve both basic and advanced problems, highlighting its newer capabilities and its support for both standard and customized solution strategies 2 - SAS: Data Discovery And Analysis With JMP 13 Pro Mia L Stephens, SAS Institute Inc, PO Box 290, York Harbor, ME, 03911, United States, mia.stephens@jmp.com JMP Statistical Discovery Software is visual and interactive desktop software for Windows and Mac, with a complete array of integrated graphical and statistical features. In this workshop we use the newly released JMP 13 Pro to demonstrate tools for data preparation, visualization, and exploration, including recode, Graph Builder®, the data filter, and geographic mapping. We’ll see how to analyze univariate, bivariate, and multivariate data, and will demonstrate tools for building and interacting with predictive models. Finally, we’ll see how to share results using HTML output and interactive web reports. Edward P Hughes, SAS Institute, Inc., Sas Institute Inc., Sas Campus Drive, Cary, NC, 27513, United States, ed.hughes@sas.com Exhibit Hall Tuesday Poster Poster Session An Optimization Algorithm For Train Timetabling Problem Based On Lagrangian Relaxation Haiying Li, Prof., Beijing Jiaotong University, Shangyuan Cun No.3, Haidian District, Beijing, 100044, China, hyli@bjtu.edu.cn, Zhengwen Liao, Jianrui Miao, Lingyun Meng The research established a cumulative flow variable-based binary programming model for train timetable optimization. A Lagrangian relaxation based time-space- state network was designed to decrease the problem scale by transforming the complicated schedule problem into a set of time-space shortest path problems of independent trains. Sparsely-sampled Hyperspectral Beam-scanning Imaging System Based On 3d Triangular Lissajous Trajectory Haonan Lin, Purdue University, West Lafayette, IN, United States, lin676@purdue.edu, Nan Kong In this work we exploited information redundancy of spatially and spectrally adjacent pixels in hyperspectral images, so as to recover the complete image with low sampling fill rate. 3D triangular wave Lissajous trajectory with high least common multiplier was used to sparsely sample the hyperspectral data cubes. Model-based image in-painting is applied to recover the complete data cubes. Results based on the sparse-sampled version of a hyperspectral coherent Raman scattering image indicates that 10% fill rate is able to recover an image without much quality degradation. Tuesday, 12:30PM - 2:30PM Poster Session

Evolution of Network-wide Traffic Dynamics Sponsored: TSL, Intelligent Transportation Systems (ITS) Sponsored Session Chair: Alireza Khani, University of Minnesota, 136 Civil Engineering Building, 500 Pillsbury Drive S.E., MInneapolis, MN, 55455, United States, akhani@umn.edu 1 - A Node Splitting-Recovery Model For Congestion Evolution Process On Road Networks Xianyuan Zhan, Purdue University, Evanston, IL, United States, zhanxianyuan@purdue.edu, Satish V. Ukkusuri, Suresh C. Rao This study presents a node splitting-recovery model for congestion evolution process on urban road networks. We introduce a new dynamic graph representation of road networks that incorporates both the network structure as well as functional states. The congestion evolution in road networks can be modeled as an equivalent node splitting-recovery process on the new graph representation. The congestion evolution data of Beijing road network are collected and used to analyze the real world congestion evolution pattern as well as the node splitting-recovery process. 2 - Doubly Dynamic Traffic Assignment Model Based On Regional Macroscopic Fundamental Diagrams Xiaozhang He, Perdue University, West Lafayette, IN, United States, seanhe@purdue.edu, Mehmet Yildirimoglu, Srinivas Peeta, Xiaozhang He This study develops a doubly dynamic traffic assignment model, incorporating within-day and day-to-day dynamics, to capture interactions between demand and supply in heterogeneously congested urban transportation networks. The model is constructed on homogenous sub-regions with static macroscopic fundamental diagrams. Numerical examples are used to investigate the properties of equilibrium states that provide insights for developing coordinated traffic management strategies. 3 - Modeling Cruising Dynamics For Downtown CurbsideParking Zhengtian Wu, University of Florida, Department of Civil and Coastal Engineering, Gainesville, FL, United States, zhengtianxu@ufl.edu, Yafeng Yin Cruising for parking not only worsens traffic conditions, but also causes additional energy consumptions and emissions. This study presents a macroscopic model for cruising dynamics in a downtown parking system. The stationary states of the system as well as their stabilities are investigated under different facility scenarios and operation strategies. The optimal occupancy of curbside parking as well as the recommendations for downtown parking management are provided.

TB90 Broadway D-Omni Health Care, Modeling X Contributed Session

Chair: Stephen Hill, University of North Carolina Wilmington, 601 South College Road, Wilmington, NC, 28403-5611, United States, hills@uncw.edu 1 - Assortment And Inventory Planning In Health Care Sector Satyaveer S Chauhan, Concordia University, 0ffice Mb11317, 1455 De Maisonneuve Boulevard West, Montreal, QC, H3G 1M8, Canada, satyaveer.chauhan@concordia.ca In this work we present a mathematical programming model to decide the number of custom trays and their contents based on past usage, preferences, cost, etc. We design custom trays for each available surgical tray. The overall model is binary integer model and we present a decomposition based approach. The model is tested on available real data set. 2 - Healthcare Distribution Response To A Zika Virus Vaccine Victor R Prybutok, University of North Texas, 1155 Union Circle,

311160, Denton, TX, 76203-5017, United States, prybutok@unt.edu, Rebecca A. Scott, Gayle Prybutok

Rapid healthcare response is analyzed for the yet developed Zika virus vaccine using a contextualized travelling salesman problem and newsvendor model. The model allows evaluation of the importance of decision making factors. Implications are reported that provide insights for increasing the ability to respond in a populated urban area.

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