2015 Informs Annual Meeting

TD75

INFORMS Philadelphia – 2015

TD76 76-Room 204C, CC Rare Event Simulation and Network Applications

4 - Bayesian Updating of Dirichlet Process Prior via Kernel Estimate Ehsan Soofi, Univesity of Wisconsin, Lubar School of Business, Milwaukee, WI, United States of America, esoofi@uwm.edu, Neshat Beheshti, Jeffrey Racine The standard nonparametric Bayesian approach uses multinomial proportions to update the Dirichlet Process Prior (DPP). We use kernel-smoothed CDF instead of the multinomial proportions for updating DPP. Applications include Bayesian measures and inferences for distributional fit and for dependence of random variables via the information measure of copula. The posterior mean of the quantized entropy provides a Bayes estimate of the dependence. TD75 75-Room 204B, CC IBM Research Best Student Paper Award IV Sponsor: Service Science Sponsored Session Chair: Ming-Hui Huang, National Taiwan University, Taiwan - ROC, huangmh@ntu.edu.tw 1 - Best Student Paper Competitive Presentation Ming-Hui Huang, National Taiwan University, Taiwan - ROC, huangmh@ntu.edu.tw Finalists of the IBM Research Best Student Paper Award present their research findings in front of a panel of judges. The judging panel will decide the order of winners, which will be announced during the business meeting of the Service Science Section at the Annual Conference. 2 - Can Objective Early Warning Scores and Subjective Risk Assessments Predict Patient’s Hospital Length of Stay and Mortality? Nasibeh Azadeh-Fard,Phd Candidate, Virginia Tech, 544 Whittemore Hall, Virginia Tech, Blacksburg VA 24061, United States of America, nasibeh@vt.edu, Jaime Camelio, Navid Ghaffarzadegan This paper presents a dynamic simulation model of patient’s health outcome and length of stay based on initial health risk and physician’s assessment of risk. Simulation results are empirically supported by analyzing a detailed dataset of 1,031 patients admitted to a large southeastern hospital in US. 3 - Dynamic Personalized Monitoring and Treatment Control of Glaucoma Pooyan Kazemian,PhD Candidate, University of Michigan-Ann Arbor, 1205 Beal Ave., Ann Arbor MI 48105, United States of America, pooyan@umich.edu, Jonathan Helm, Mariel Lavieri, Joshua Stein, Mark Van Oyen, We develop an innovative modeling framework for chronic disease patients to help guide clinicians to quickly detect disease progression and adjust the treatment plan over time to limit disease progression. The model is able to (1) optimize the time interval between sequential monitoring tests; (2) specify the best set of tests to take during each patient’s office visit; and (3) provide target values for the controllable disease risk factors. Glaucoma is discussed as a case study. 4 - Evaluating Consumer m-Health Services for Promoting Healthy Eating: A Randomized Field Experiment Yi-Chin Lin,CMU, 5000 Forbes Avenue, Pittsburgh PA 15213, United States of America, yichinl@cmu.edu, Vibanshu Abhishek, Julie Downs, Rema Padman Mobile apps have great potential to provide promising services to improve consumers’ engagement and behaviors. Focusing on healthy eating, this study shows that an image-based professional support greatly improves consumer engagement and eating behaviors, while social media and a heuristic approach of self-management might have negative effects in some occasions. 5 -Dynamic Matching in a Two-Sided Market Yun Zhou,University of Toronto, 105 St. George Street, Toronto, ON, Canada, Yun.Zhou13@Rotman.Utoronto.ca, Ming Hu A two-sided market often shares a common structure that engages three parties: the supply side, the demand side and an intermediate firm facing intertemporal uncertainty on both supply/demand sides. We propose a general framework of dynamically matching supply with demand of heterogenous types (with horizontally or vertically differentiated types as special cases) by the intermediary firm and explore the optimal and heuristic matching policies.

Sponsor: Simulation Sponsored Session

Chair: John Shortle, George Mason University, 4400 University Dr., MSN 4A6, Fairfax, VA, United States of America, jshortle@gmu.edu 1 - Rare-event Simulation for Queues with Time-varying Arrivals Ni Ma, Columbia University, 500 West 120th Street, Room 345, New York, NY, 10027, United States of America, nm2692@columbia.edu, Ward Whitt We show that the exponential tilting approach for rare-event simulation in the GI/G/1 queue can also be applied to efficiently estimate the time-varying periodic-steady-state probability of large delays in a Mt/GI/1 single-server queue with periodic arrival rate function. 2 - Green Simulation Designs for Repeated Experiments Mingbin Feng, PhD Candidate, Northwestern University, 2145 Sheridan Rd, Rm C210, Evanston, IL, 60208, United States of America, benfeng@u.northwestern.edu, Jeremy Staum In many applications of simulation, such as in financial risk management, experiments are usually repeated with similar inputs. In these cases simulation outputs should be viewed as useful resource that should be recycled and reused to improve the efficiency of subsequent experiments. We consider a periodic credit risk evaluation problem in the KMV model and the numerical results show improving accuracy over time, measured by mean squared error, as more and more outputs are recycled. 3 - A General Golf Course Simulation Tool: Keeping Delays Down and throughput Up Moonsoo Choi, Columbia University, Department of Industrial Engineering, New York, NY, 10027, United States of America, mc3983@Columbia.edu, Qi Fu, Ward Whitt We describe a simulation tool for designing and managing golf courses. Group play is represented by eighteen queues with precedence constraints, in series, where the primitives are the random group playing times on each stage of a hole. We characterize balanced courses and show the advantages over unbalanced courses. 4 - Rare-event Simulation for Vulnerability Analysis of Power Grids John Shortle, George Mason University, 4400 University Dr., Vulnerability of a power grid can be evaluated by systematically considering failures of individual elements and estimating the likelihood of a large-scale blackout following these initial failures. This talk presents a method for identifying vulnerable links by using a low-fidelity model of the power system to guide simulation of a higher-fidelity model. Numerical examples using real power systems are given. MSN 4A6, Fairfax, VA, United States of America, jshortle@gmu.edu, Jie Xu, Chun-hung Chen

TD77 77-Room 300, CC Supply Chain Optimization Contributed Session

Chair: Robert Russell, Professor of Operations Management, Univ. of Tulsa, 800 S Tucker Drive, College of Business, Tulsa, OK, 74104, United States of America, rrussell@utulsa.edu 1 - A Practical Application of Large-Scale Capacitated Facility Location Uday Rao, Professor, OBAIS Department, College of Business, University of Cincinnati, Cincinnati, OH, 45221, United States of America, uday.rao@uc.edu, Amit Raturi, Maria Caridi We study a large-scale capacitated facility location problem motivated by interaction with a company in the US MidWest. The problem has 1000 locations with demand seasonality, several facility types differing in capacity, fixed installation and variable operating costs, and transportation costs depending on transportation speed / mode selected. We present solution approaches using mathematical programming, clustering and quick heuristics. We test sensitivity to problem parameters.

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