2016 INFORMS Annual Meeting Program

WB20

INFORMS Nashville – 2016

WB18 106A-MCC DMA General Contributed Session Chair: Jose M. Merigo, Full Professor, University of Chile, Av. Diagonal Paraguay 257, Santiago, 8330015, Chile, jmerigo@fen.uchile.cl 1 - Cyber Attacker Choices In A Three-way Behavioral Security Game Jinshu Cui, University of Southern California, 3620 McClintock This study focuses on cyber attackers’ choices in a security game involving attackers, defenders, and users. An attacker can choose to attack the defenders or the users. Deterrence is measured by the third option of the attacker - no attack. Conversely, the defenders and users can select either a standard or enhanced security level. We conducted a behavioral experiment in which 497 subjects played as attackers over 30 rounds of the game and were incentivized based on their performance. Defenders’ and users’ joint strategies were manipulated. Results indicated that subjects were more likely to hack database when EV(database) was higher, and were more deterred when both EVs were negative. 2 - Sequential Decisions Following Near Misses Jinshu Cui, University of Southern California, 3620 McClintock Avenue, # 501, Los Angeles, CA, 90089, United States, jinshucu@usc.edu, Richard S John Prior near miss experiences have been identified as a contributing factor in responses to risks of disasters. Researchers found a near miss event could lead individuals to interpret the risk as either “vulnerable” or “resilient”, while had no conclusions on what could lead to different interpretations. The current study hypothesizes that responses to near miss events are determined by psychological distance. We conducted a behavioral experiment in which 100 subjects were exposed to a sequence of 20 events. Results indicated that subjects were less likely to engage in protective measures when a near miss event is psychological distant to the decision maker and when more near misses were experienced. 3 - Column Generation For Airline Crew Rostering: Practical Considerations In A Production System Andreas Westerlund, Optimization Expert, Jeppesen, Odinsgatan 9, Gothenburg, 411 03, Sweden, andreas.westerlund@jeppesen.com Jeppesen’s crew rostering optimizer is today used by around 40 airlines to produce monthly schedules for their flying crew. The optimizer allows the user to configure various kinds of business logic and it solves monthly schedules for problem instances with above 20k crew-members and 100k activities. In this presentation we will start by defining the rostering optimization problem in general. Then we will describe our column generation framework that is used to deal with it. Finally we will look at the specific problem of having an efficient fixing process in the presence of high degree of symmetry. 4 - The Internet Of Things: Preliminary Research Results Gary D Scudder, Vanderbilt University-OGSM, 401 21st Avenue South, Nashville, TN, 37203-2422, United States, gary.scudder@owen.vanderbilt.edu, Sal March In this research, we look at the emerging field of the Internet of Things and develop a research agenda for managerial issues. In addition, we will discuss research in IoT for preventive maintenance. IoT is shown to be beneficial in reducing costs and increasing profits. 5 - The Ordered Weighted Average Division Jose M. Merigo, Full Professor, University of Chile, Av. Diagonal Paraguay 257, Santiago, 8330015, Chile, jmerigo@fen.uchile.cl, Sigifredo Laengle, Ronald R Yager The ordered weighted average division is an aggregation operator that aggregates a set of divisions providing a parameterized family from the minimum to the maximum division. The work considers a wide range of particular cases including the average division, the median division and the weighted average division. It also develops some further extensions including the weighted ordered weighted average division and the generalized weighted ordered weighted average division. This approach can be applied in a wide range of problems dealing with the aggregation of divisions including decision making and computational intelligence. Avenue, # 501, Los Angeles, CA, 90089, United States, jinshucu@usc.edu, Richard S John, Heather Rosoff

WB19 106B-MCC Future of Disease Modeling in Clinical and Public Health Sponsored: Computing Sponsored Session Chair: Zeynep Ertem, University of Texas-Austin, University of Texas- Austin, Austin, TX, United States, zeynepsertem@gmail.com 1 - Pandemic Influenza Preparedness David Morton, Northwestern University, david.morton@northwestern.edu We describe three data-driven optimization models that inform resource allocation in preparing for an influenza pandemic. In particular, we optimize: the mix of central and regional stockpiles of ventilators, accounting for stochastic peak-week demand; the spatial allocation of antivirals, considering under-insured populations and hard-to-reach locations; and, the spatial allocation of multiple types of vaccines with differing suitability for each prioritized target population. We discuss challenges and extensions. 2 - Role Of Operations Research In Chronic Disease Management Mariel Lavieri, University of Michigan, lavieri@umich.edu I discuss past and future challenges encountered in managing chronic diseases. 3 - Mathematical Models for Cancer Screening Fatih Safa Erenay, University of Waterloo, ferenay@uwaterloo.ca My talk will provide an overview of models proposed for the optimal cancer screening problem from societal and personal perspectives. I will start with the classical models that schedule screening interventions over a planning horizon, and describe the evolution of the literature towards more dynamic, partially observable, and personalized models over examples from colorectal cancer screening. The talk will also highlight the current challenges and recent trends in cancer screening literature. Assets and Structured Hedges in Energy Markets Severe Incompleteness and Methods for Dealing with It Invited: Tutorial Invited Session Chair: Glen Swindle, Scoville Risk Partners, 405 Lexington Avenue, 21st Floor, New York, NY, 112, United States, glenswindle@scovilleriskpartners.com 1 - Assets And Structured Hedges In Energy Markets – Severe Incompleteness And Methods For Dealing With It Glen Swindle, Scoville Risk Partners, 405 Lexington Avenue, 21st Floor, New York, NY, 12, United States, glenswindle@scovilleriskpartners.com Risks in energy markets are inherently high dimensional due to large numbers of delivery locations and physical attributes, stochastic demand, and seasonality. In contrast, the number of instruments with sufficient liquidity to support hedging activities is relatively small, and has never been able to span the set of risks sustained by market participants. This mismatch has spawned an interesting and arguably unique set of challenges related to the valuation and hedging of energy portfolios. Here we will survey examples of such, including variable quantity swaps, generation and structured asset hedges. WB20 106C-MCC

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