Informs Annual Meeting Phoenix 2018

INFORMS Phoenix – 2018

MA13

2 - Cash Hedging in a Supply Chain Yixuan Xiao, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong, Panos Kouvelis, Xiaole Wu We study hedging cash flow risks in a supply chain where firms invest internal funds to improve production efficiencies. We offer a decomposition framework to capture the cost reduction and flexibility effect of hedging. It allows us to understand how a firm’s hedging choice depends on its supply chain partner’s decision, and how such interaction is affected by supply chain characteristics such as market size, cash flow volatility and correlation. 3 - Financial Incentives to Avoid Major Quality Problems in a Supply Chain Matthew Sobel, Case Western Reserve University, Cleveland, OH, United States, Susan Slotnick Manufacturers who outsource components incur risks as well as benefits. If the supplied product has a major quality defect, the adverse effect on the manufacturer’s reputation reduces its market share. This paper presents a discrete-time model of a buyer who collaborates with a sole supplier to avoid quality problems by paying a higher per-unit purchase price to the supplier and/or paying the supplier a lump sum contingent on the absence of a major quality defect. Analytical results include an optimal risk-posture policy for which the buyer should use only one of these financial incentives or the other. Computational results provide insights about the relationship of that optimal policy to various parameters. Chair: Aaron Lott, D-Wave Systems Inc., Palo Alto, CA, 9, United States 1 - Towards Quantum-assisted Optimization and Machine Learning on Google Quantum Cloud Masoud Mohseni, Google Quantum AI Lab, Venice Beach, CA, United States We present an overview of our progress quantum optimization and machine learning at Quantum AI Lab at Google. In particular, we present an end-to-end quantum-assisted optimization engine on Google Cloud Platform. Our physics- inspired approaches use an interplay of thermal and quantum fluctuations to sample from inaccessible low-energy states of spin-glass systems that encode certain hard combinatorial optimization and probabilistic inference problems. We also introduce universal discriminative quantum neural networks for classification and purification of quantum data. 2 - Leveraging Mixed Integer Programming for Evaluating D-Wave Solution Quality Carleton Coffrin, Los Alamos National Laboratory, Los Alamos, NM, United States Unconstrained Binary Quadratic Programs are a challenging class of NP-Hard discrete optimization problems with a wide variety of real-world applications and established solution methods. This work compares the performance of established Integer Programming solvers, a state-of-the-art Large Neighborhood Search heuristic, and a D-Wave QPU on a variety of BQP problem classes from the literature. The computational results suggest that the D-Wave QPU consistently produces high-quality solutions with runtimes that are comparable to the established methods. 3 - Quantum Machine Learning at the Creative Destruction Lab Eric Brown, Creative Destruction Lab, Toronto, ON, Canada Now is a critical time for the emerging technology of quantum computing. Progress in the field is being fueled increasingly by industry players seeking to capitalize on its disruptive potential. At the Creative Destruction Lab (CDL), through our Quantum Machine Learning initiative, we are incubating pre-seed ventures pursuing commercial quantum computing and its intersection with machine learning. In this talk I will introduce modern quantum computing, the CDL’s approach to developing its landscape, and some of the applications being pursued by our quantum alumni ventures. 4 - Putting Quantum Computing in Your Toolbox Aaron Lott, D-Wave Systems Inc., Palo Alto, CA, United States We present an overview of the D-Wave 2000Q quantum computer architecture and discuss several novel optimization and machine learning algorithms that have been designed to leverage current and future D-Wave quantum computers. We describe the interplay between statistical physics, quantum annealing, Bayesian inference and Boltzmann machines to provide insights into areas where quantum computation and quantum simulation will play a key role in solving data-driven real-world problems. n MA12 North Bldg 126A Quantum Computing Emerging Topic: OR Frontiers Emerging Topic Session

n MA13 North Bldg 126B Healthcare Operations Sponsored: Manufacturing & Service Oper Mgmt/Healthcare Operations Sponsored Session Chair: Michael Freeman, INSEAD, Singapore 1 - The Impact of New Service Delivery Models on Work Hours and Quality Hessam Bavafa, Wisconsin School of Business, 4284C Grainger Hall, 975 University Avenue, Madison, WI, 53706, United States, Christian Terwiesch In many professional services, an expert server such as a physician or lawyer delivers services to customers across multiple channels: in-person meetings, phone calls, and emails. In these settings, there exists a risk that work obligations encroach on the personal lives of the experts and that the quality of their work might suffer. We empirically examine these concerns in the setting of physicians providing care to patients via two channels: in-person office visits and online e- visits. Our data include 3.4 million patient encounters (more than one million of which are e-visits) covering a 8.5-year timespan. 2 - The Impact of Bundled Payment Policy on Healthcare Operations: Evidence from China Jingui Xie, University of Science and Technology of China, School of Management, 96 Jinzhai Road, Hefei, 230026, China, Yiming Fan, Jingqi Wang The paper studies the impact of bundled payment on health care spending, utilization, and quality, by using insurance claim data. We provide new evidence from China on the impact of bundled payment versus fee-for-service on health care operations. Our main results show that bundled payment reduces medical cost and length of stay in general, while increases readmission and revisit rates. Our results show that cost reduction in provincial hospitals is significant while the quality of care is maintained. However, the medical cost in country hospitals was not reduced after the implementation of bundled payment. 3 - Physician Leadership and Operational Strategies: Focus, Volume and Concentration in General Hospitals Sandra S lz, Erasmus University, Rotterdam, Netherlands, Ludwig M. Kuntz, Michael Wittland We consider the role of physicians in leadership positions and their influence on operational strategies pursued in general hospitals. We distinguish between volume strategies, focus strategies, and internal routing strategies and analyze how the involvement and the turnover rate of the medical director is related to the choice of these strategies. 4 - Continuity of Care versus a Second Opinion: Evidence from the Opioid Crisis Katherine Bobroske, Cambridge Judge Business School, Trumpington Street, Cambridge, CB2 1AG, United Kingdom, Michael Freeman, Lawrence Huan, Stefan Scholtes In the US, mortality from the opioid crisis is quickly eclipsing the AIDS epidemic, taking an estimated 49,000 lives in 2017 alone. Despite risk warnings, opioids continue to be frequently used in general practice. We investigate the impact of continuity of care versus a second opinion for patients with a first opioid prescription. Continuity of care is generally commended as a single doctor has full oversight into the patient’s treatment plan. However, in the context of opioids, it may be difficult for a doctor who prescribed the first opioid to transition the patient to a different treatment. Using a nationwide dataset, we find that the second opinion may be a critical tool in curbing opioid dependence.

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