2016 INFORMS Annual Meeting Program

SA02

INFORMS Nashville – 2016

SA02 101B-MCC Healthcare Analytics and Medical Decision Making Sponsored: Data Mining Sponsored Session Chair: Hasan Kartal, University of Massachusetts Lowell, One University Avenue, Lowell, MA, 01854, United States, Hasan_Kartal@uml.edu 1 - PPMF: A Patient-based Predictive Modeling Framework For Early ICU Mortality Prediction Mohammad Amin Morid, The David Eccles School of Business, University of Utah, 130 University Village, Salt Lake City, UT, United States, amin.morid@business.utah.edu, Olivia R. Liu Sheng, Samir Abdelrahman This paper presents a patient based predictive modeling framework (PPMF) to improve the performance of early ICU mortality prediction. PPMF consists of three main components. The first component captures dynamic changes of patients’ status in the ICU using their time series data. The second component is a local approximation algorithm that classifies patients based on their similarities. The third component is a Gradient Decent wrapper that updates feature weights according to the classification feedback. Experiments show that PPMF significantly outperforms: (1) the severity score systems, (2) the aggregation based classifiers, and (3) baseline feature selection methods. 2 - The Emergency Response Community Effectiveness Modeler: A Simulation Modeling Tool To Analyze EMS vs. Smartphone-based Samaritan Response Michael Khalemsky, Graduate School of Business Administration, Bar Ilan University, Ramat Gan, Israel, khalemsky@gmail.com, David G. Schwartz Smartphones and location-based social networking technologies present an opportunity to re-engineer certain aspects of emergency medical response by establishing Emergency Response Communities (ERC). The ERC Effectiveness Modeler (ERCEM) estimates the efficacy of smartphone-based Samaritan response for given medical condition and geographic region. The ERCEM uses parameters such as population density, prescription adherence, smartphones penetration etc. and performs Monte Carlo simulation to compare potential ERC response to traditional EMS response. We present the modeler and show how it assessed effectiveness of ERC for anaphylaxis in the USA based on data from the NEMSIS project. 3 - Public Health Data Sharing With Privacy Protection Hasan Kartal, Manning School of Business, University of Massachusetts Lowell, Lowell, MA, 01850, United States, hasan_kartal@uml.edu This study examines privacy disclosure risks in health data when patients have multiple records in a dataset. Existing data privacy approaches typically assume that each individual in a dataset corresponds to a single record, which tends to underestimate the disclosure risks in the multiple-record problems. We propose a new privacy measure, called g-balance, and develop an efficient algorithm based on the g-balance measure to protect against the multiple-record linkage attacks. The effectiveness of the proposed approach is demonstrated in an experimental study using real-world data.

3. Household-level Economics Of Scale In Transportation Mehdi Behroozi, Northeastern University, Boston, MA, 02115, United States, behro040@umn.edu 4. Online Decision-Making With High-Dimensional Covariates Hamsa Bastani, Stanford University, Stanford, United States, bayati@stanford.edu Big data has enabled decision-makers to tailor choices at the individual-level in a variety of domains such as personalized medicine and online advertising. This involves learning a model of decision rewards conditional on individual-specific covariates. In many practical settings, these covariates are high-dimensional; however, typically only a small subset of the observed features are predictive of a decision’s success. We formulate this problem as a multi-armed bandit with high- dimensional covariates, and present a new efficient bandit algorithm based on the LASSO estimator. Our regret analysis establishes that our algorithm achieves near- optimal performance in comparison to an oracle that knows all the problem parameters. The key step in our analysis is proving a new oracle inequality that guarantees the convergence of the LASSO estimator despite the non-i.i.d. data induced by the bandit policy. Furthermore, we illustrate the practical relevance of our algorithm by evaluating it on a real-world clinical problem of warfarin dosing. 5 - Distributionally Robust Stochastic Optimization With Wasserstein Distance Rui Gao, Georgia Institute of Technology, Atlanta, GA, United States, rgao32@gmail.com Electricity Markets and Contract Design Sponsored: Energy, Natural Res & the Environment, Energy I Electricity Sponsored Session Chair: Edward James Anderson, University of Sydney, H70 - Abercrombie Building, Sydney, NSW 2006, Australia, edward.anderson@sydney.edu.au 1 - Retail Equilibrium With Switching Consumers In Electricity Markets Carlos Ruiz Mora, Universidad Carlos III de Madrid, Madrid, Spain, caruizm@est-econ.uc3m.es, F. Javier Nogales, F. Javier Prieto We consider a game theoretical model where asymmetric retailers compete in prices to increase their profits by accounting for the utility function of switching consumers. Consumer preferences for retailers are uncertain and distributed within a Hotelling line. We analytically characterize the equilibrium of a retailer duopoly, establishing its existence and uniqueness conditions for a wide class of utility functions. The duopoly model is extended to a multiple retailer case. 2 - Flow-based Market Coupling In The European Electricity Market Mette Bjørndal, Professor, NHH Norwegian School of Economics, Bergen, Norway, Mette.Bjorndal@nhh.no From May 2015, the Flow-Based Market Coupling (FBMC) model replaced the Available Transfer Capacity (ATC) model in parts of the European power market. The FBMC model aims to enhance market integration and to better monitor the physical power flow, and it is expected to lead to increased social welfare in the day-ahead market and more frequent price convergence between different market zones. This paper gives a discussion on mathematical formulations of the FBMC model and the procedures of market clearing. We examine the FBMC model in two test systems and show the difficulties of implementing the model in practice. 3 - Negotiating Forward Contracts With Private Information Edward James Anderson, University of Sydney, edward.anderson@sydney.edu.au We consider the use of forward contracts to reduce risk for firms operating in a spot market. Firms have private information on the distribution of prices in the spot market. We discuss different ways in which firms may agree on a forward contract (offers to a broker and direct bargaining). We also discuss an equilibrium in which two firms each offer a supply function and the clearing price and quantity for the forward contracts are determined from the intersection. In this context a firm can use the offer of the other player to augment its own information about the future price. It is interesting that these sophisticated strategies are likely to produce worse outcomes for both firms. SA04 101D-MCC

SA03 101C-MCC

Nicholson Student Paper Prize I Invited: Nicholson Student Paper Prize Invited Session

Chair: Maria Esther Mayorga, North Carolina State University, 400 Daniels Hall, Raleigh, NC, 27695, United States, memayorg@ncsu.edu 1 - Nicholson Student Paper Prize Maria Esther Mayorga, North Carolina State University, Dept. of Industrial & Systems Engineering, Raleigh, NC, 27695, United States, memayorg@ncsu.edu This session highlights the finalists for the 2016 George Nicholson Student Paper Competition. 2 - A Necessary and Su cient Condition for Throughput Scalability of Fork and Join Networks with Blocking Yun Zeng, Ohio State University, Columbus, OH, United States, zeng.153@buckeyemail.osu.edu, Augustin Chaintreau, Don Towsley, Cathy Xia

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