2016 INFORMS Annual Meeting Program

WA32

INFORMS Nashville – 2016

WA32 203A-MCC Risk Analysis I Contributed Session

4 - Optimal Workload Management During A Physician’s Shift In Emergency Departments

Zhankun Sun, University of Calgary, zhankun.sun@haskayne.ucalgary.ca

ED physicians can adjust their workload, which is measured by the number of patients signed up, to reduce patient handovers at the end of their shift. Patient handovers raise safety concerns due to the discontinuation of care. We present a dynamic programming model to inform patient flow management during a single ED physician’s work shift. Case studies based on real data will also be discussed. WA31 202C-MCC Service Management: Economics and Operations Sponsored: Manufacturing & Service Oper Mgmt, Service Operations Sponsored Session Chair: Achal Bassamboo, Northwestern University, Kellogg School of Management, Northwestern University, Evanston, IL, 60208, United States, a-bassamboo@northwestern.edu C-Chair: Ramandeep Randhawa, University of Southern California, Marshall School of Business, University of Southern California, Los Angeles, CA, 90089, United States, ramandeep.randhawa@marshall.usc.edu 1 - Scheduling Networks With Synchronization Constraints And Heterogeneous Customers Amy R Ward, Professor, University of Southern California, Marshall School of Business, Bridge Hall BRI 401H, Los Angeles, CA, 90089-0809, United States, amyward@marshall.usc.edu, Erhun Ozkan Networks in which the processing of jobs occurs both sequentially and in parallel are prevalent in many applications domains, such as computer systems, healthcare, and manufacturing. The relevant control decision is how to dynamically determine job priority at the servers that process multiple job types. A key difficulty in finding a delay-minimizing control is that the parallel processing of jobs gives rise to synchronization constraints. We propose a state- dependent departure pacing control under which job priorities are determined so as to balance the jobs waiting to be joined at the synchronization servers. We prove our control is asymptotically optimal for certain network topologies. 2 - Collaboration And Multitasking In Networks: Aligning Task Priorities And Collaboration Levels Itai Gurvich, Kellogg School of Management, i-gurvich@kellogg.northwestern.edu, Jan A Van Mieghem We study networks where some tasks require the simultaneous processing by multiple types of multitasking indivisible resources. As one maximizes capacity, we prove, the achievable performance space collapses into a single policy.: the highest priority must be given to the tasks that require the most collaboration: a mismatch between priority levels and collaboration levels inevitably inflicts a capacity loss. We further establish a fundamental difference between the achievable performance spaces of preemptive and non-preemptive collaborative networks. 3 - The Costs And Benefits Of Ridesharing: Sequential Individual Rationality And Sequential Fairness Ragavendran Gopalakrishnan, Research Scientist, Xerox Research Centre India, Bangalore, India, Ragavendran.Gopalakrishnan@xerox.com, Koyel Mukherjee, Theja Tulabandhula We formulate a cost sharing framework for ridesharing that explicitly takes into account the inconvenience costs of passengers due to detours. We then introduce a notion of sequential individual rationality (SIR) that requires that the disutilities of existing passengers decrease as additional passengers are picked up, and show that these constraints induce a natural limit on the permissible incremental detours as the ride progresses. We characterize routes for which there exists some cost sharing scheme that is SIR on that route, and explore the consequences of SIR on the design of sequentially fair cost sharing schemes. We conclude by addressing the algorithmic challenges associated with SIR. 4 - Scheduling Impatient Customers Based on Time In Queue Achal Bassamboo, Northwestern University, a-bassamboo@northwestern.edu, Ramandeep Randhawa We study scheduling impatient customers in multi-class parallel server queueing systems. From the system’s perspective, customers that are of the same class at time of arrival get further differentiated on their residual patience time as they wait in the system. Using a fluid approach, we propose a novel cost-minimizing policy that schedules customers on two dimensions of heterogeneity: class and time-in-queue information.

Chair: Ming Zhou, Professor, Shenzhen University, College of Management, Shenzhen, 518060, China, mzhou@szu.edu.cn 1 - Optimal Capital Requirements In Financial Networks With Fire Sales Jongsoo Hong, Duke University, 100 Fuqua Drive, Durham, NC, 27707, United States, jh176@duke.edu We consider an interbank network with fire sales externalities of multiple illiquid assets and study the problem of optimally trading off between capital reserves and systemic risk. We find that the optimal capital requirements under maximum payments and prioritized liquidation rule can be formulated as a convex and convex mixed integer programming, respectively. To solve the convex MIP, we offer an iterative algorithm that converges to the optimal. We show the results of the methodology on numerical examples and provide implications for capital regulation policy and stress test. 2 - A New Approach To Fuzzy Risk Assessing Large Renewable Energy Construction Projects Jose-Ignacio Munoz-Hernandez, University of Castilla - La Mancha, Edifico Politecnico - UCLM, Avda Camilo Jose Cela, S/N, Ciudad Real, 13071, Spain, joseignacio.munoz@uclm.es, Luis Serrano-Gomez The Fuzzy Sets Theory deals with simple linguistic terms in order to classify the level of an impact or a probability in risk assessing. Expressions like “Moderate Impact” or “Very High Probability” are more clear and intuitive to experts for carrying out risk assessments than the use of numerical values. However, idiomatic expressions are not useful to calculate severity or probability levels accurately. This work uses Fuzzy Logic and Monte-Carlo simulation not only to evaluate those expressions numerically but also to calculate experts evaluations coherence, weighing up their results according to the coherence level in their responses. 3 - Accounting For Heterogeneity And Macroeconomic Variables In The Estimation Of Transition Intensities For Credit Cards Jonathan Crook, University of Edinburgh, Business School, 29 Buccleuch Place, Edinburgh, EH8 9JS, United Kingdom, j.crook@ed.ac.uk, Viani Djeundje The literature has considered intensity models that give predictions of the probability, for each customer, that he/she will transit from one state of delinquency to another between any two months in the life of the loan. The transitions include not only transitions into further delinquency but also transitions to lesser states of delinquency, that is cure. We now extend this work by including frailty terms relating to the individual cases. This means that any statistical bias that may exist because of the omission of unobserved effects due to these types of variation should be removed. Results of applying the method to a Gwendolyn K Lee, Chester C. Holloway Professor, University of Florida, Gainesville, FL, 32611, United States, gwenlee@ufl.edu, Ye Xia Firms’ risk strategy involves choosing a probability of success/failure in realizing a certain size of impact on the firm’s competitive strength. We observe a disturbing pattern general across a broad family of shapes of risk distribution (e.g., changing from Gaussian to Pareto distributions where the tails of the distribution become longer or heavier). One and one firm only always chooses to take risks that carry the possibility of inflicting extreme privacy harm. The risk strategy does not shift as the risk-return distribution changes its shape. The risk strategy for managing information privacy is studied in the context of firms pursuing data-intensive innovation such as personalized medicine. large dataset relating to credit card holders will be illustrated. 4 - Risk Strategy For Managing Information Privacy

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