2015 Informs Annual Meeting

TA36

INFORMS Philadelphia – 2015

TA36 36-Room 413, Marriott Innovations on Disaster Response Logistics Sponsor: Public Sector OR Sponsored Session Chair: Felipe Aros-Vera, arosvm2@rpi.edu 1 - Competition Over Funding Resources in Humanitarian Operations Arian Aflaki, Doctoral Student, Duke University, 100 Fuqua Drive, Box 90120, Durham, NC, 27708, United States of America, arian.aflaki@duke.edu, Alfonso Pedraza-Martinez Donors seek control over their donations, while it hurts the operational efficiency of Humanitarian Organizations (HOs). We model the trade-off between operational performance, fundraising effort, and donor preferences and find that HOs can benefit from limiting donors’ control over their donations; however, competition forces HOs to give control to donors. 2 - Optimizing Humanitarian Logistics Concepts of Operations: The Case of Haiti Erica Gralla, Assistant Professor, George Washington University, 800 22nd Street NW, Washington, 20052, United States of America, egralla@gwu.edu, Liam Cusack, Phillip Graeter After a disaster, the Logistics Cluster coordinates logistics for various responding humanitarian agencies. They must quickly set up a supply chain, determining entry points, major transport corridors, storage hubs, and vehicle requirements. This research supports these decisions by finding the minimum-cost supply chain configuration. Results for the case of Haiti are presented. 3 - Assessment of Risk Management and Disaster Response Capabilities through the Process Maturity Framework Miguel Jaller, Assistant Professor, University of California, Davis, One Shields Ave, Ghausi Hall, 3143, Davis, CA, 95616, United This paper explores the Process Maturity Framework to assess the current state of the risk management and disaster response capabilities of a region in a developing country. Using data collected by the team in Colombia, the paper discusses the results in terms of the maturity levels for the different factors that comprise the processes of: risk management and understanding, risk mitigation, and disaster management and response; and puts forward a number of achievable goals and key practices. 4 - Adaptive Decision Making under Dynamic Information Update in Limited Data Environments Kezban Yagci Sokat, PhD Candidate, Northwestern University, 2145 Sheridan Road, C210, Evanston, IL, 60208, United States of America, kezban.yagcisokat@u.northwestern.edu, Irina Dolinskaya, Karen Smilowitz After a disaster, there is often limited information about infrastructure damage. New data sources such as OpenStreetMap are emerging. Utilizing these new data sources, we use clustering and various imputation techniques with pre-disaster and post-disaster attributes to approximate incomplete information in a timely manner for routing decisions. TA37 37-Room 414, Marriott Health Care Modeling and Optimization IX Contributed Session Chair: Parastu Kasaie, Postdoctoral Fellow, Johns Hopkins University, 615 N. Wolfe St, E6039, Baltimore, MD, 21205, United States of America, pkasaie@jhu.edu 1 - Dynamic Advance Overbooking with No-Shows and Cancellations Van-Anh Truong, Columbia University, 500 West 120th St, New York, NY, 10027, United States of America, vt2196@columbia.edu We introduce the first tractable model of dynamic advance overbooking with no- shows and cancellations. In this fundamental model, advance appointments must be given to a stream of patients arriving randomly over time. Patients might cancel or miss their appointments, with the likelihood of these events increasing with their wait times. 2 - Integrating Quick-response Methods and Staffing Decisions in a Hospital Jan Schoenfelder, Research Assistant, Augsburg University, States of America, mjaller@ucdavis.edu, Diego Suero, Melissa Del Castillo, Nuris Calderón, Jose William Penagos

We present an optimization model that combines hospitals’ nurse staffing decisions with two classes of quick-response decisions: (i) adjustments to the assignment of cross-trained nurses working the current shift in each unit and (ii) transfers of patients between units and off-unit admissions. We use a simulation to derive insights into the level of benefit that can be expected from integrating the aforementioned quick-response methods in the staffing process. 3 - Analyzing the Relationship Between Two-phased Room Allocation Policies in an Outpatient Clinic Vahab Vahdatzad, PhD Candidate, Northeastern University, 360 Huntington Avenue, Boston, MA, 02215, United States of America, vahdatzad.v@husky.neu.edu, James Stahl, Jacqueline Griffin This research analyzes the relationship between two phases of room assignment in an outpatient clinic. Specifically, we studied the interplay between the use of rooms for Medical Assistant and physicians during a patient visits. We demonstrate that policies for assigning rooms to MA and physicians has a significant impact on patient wait time and length of stay. Several room allocation policies are examined using discrete event simulation and interactions between two phases are investigated. 4 - An Agent-Based Simulation Model of HIV Transmission and Control among Men who have Sex with Men in Baltimore City Parastu Kasaie, Postdoctoral Fellow, Johns Hopkins University, 615 N. Wolfe st, E6039, Baltimore, MD, 21205, United States of America, pkasaie@jhu.edu, David Dowdy We present an agent-based simulation model to project the population-level impact of implementing HIV preventive therapy (PREP) and treatment (ART) for high-risk men who have sex with men (MSM) in Baltimore city. We compare a counterfactual scenario in which PrEP and ART continue to be used at current (low) levels against scenarios in which different levels of coverage and adherence are achieved. The primary outcome of interest is the HIV incidence among MSM in Baltimore over five years. 5 - Estimating the Energy Imbalance Characterizing the Rise in Obesity Among Adults in England Saeideh Fallah-Fini, California State and Polytechnic University, Pomona, 3801 W. Temple Ave, Pomona, CA, 91768, United States of America, sfallahfini@cpp.edu This paper uses systems dynamics to present a population-level model that quantifies the energy imbalance gap responsible for the obesity epidemic among adults in England (across different gender and ethnicity subpopulations) during the past two decades. The developed model also estimates the magnitude of calorie reduction that should be targeted by obesity interventions to reverse the current trajectory of the obesity epidemic. TA39 39-Room 100, CC Supply Chain Management and Marketing Interface Cluster: Operations/Marketing Interface Invited Session Chair: Gangshu Cai, Santa Clara University, OMIS Department, Lucas Hall 216N, Santa Clara, CA, 95053, United States of America, gcai@scu.edu 1 - Effects of Demand Uncertainty and Production Lead Time on Product Quality and Firm Profitability Baojun Jiang, Olin Business School, Washington University in St. Louis, MO, 63130, United States of America, baojunjiang@wustl.edu, Lin Tian We study the effects of demand uncertainty and production lead time in a distribution channel with one retailer outsourcing its production to one supplier. We show that the supplier may have no incentive to improve its lead time even if it is costless to do so. An increase in the supplier’s JIT production capacity can lead to higher or lower product quality, benefiting the retailer but potentially hurting the supplier. A better market can make both the supplier and the retailer worse off. 2 - The Protection Economy: Problem Retention or Problem Prevention? Oded Koenigsber, Associate Professor, London Business School, Regent’s Park, London, United Kingdom, okoenigsberg@london.edu, Eitan Gerstner, Daniel Halbheer Companies are advised to invest in quality programs to solve and prevent customer problems. This paper shows that profit-maximizing motivate companies to peruse protection strategies under which customer problems are created or preserved so that protection services can be offered to repair the damages created through the problems. Thus, standard economic efficiency measures used in the “solution economy” are inappropriate for the “protection economy”.

Neusässer Strafle 47, Augsburg, Ba, 86156, Germany, janschoe@indiana.edu, Daniel Wright, Edwin Coe, Kurt Bretthauer

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