Informs Annual Meeting 2017

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INFORMS Houston – 2017

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3 - Optimal Size of a Combined Heat and Power Generator for an Industrial Firm Wenbin Wang, Shanghai University of Finance and Economics, Shanghai, China, wang.wenbin@mail.shufe.edu.cn, Gilvan Souza, Owen Wu We consider a manufacturer who uses both steam and electricity in its primary production process makes investment on a Combined Heat and Power (CHP) system. We provide a decision model and find the optimal capacity and operating policy for a CHP system that reduce the total investment and energy costs. 4 - Is Electricity Storage Green? A Study on the Commercial Sector Electricity storage facilities, such as industrial batteries, are considered the “game changer” in de-carbonizing the electrical grid. They are being widely installed in the commercial sector, e.g., retail stores and corporate offices. We model the problem of managing electricity storage in a commercial building for both the cases with and without a solar photovoltaic system. Our numerical results, based on models calibrated to electricity load data for more than 70 commercial buildings in the U.S., show that for all these buildings, optimal storage operations may increase carbon emissions. We also study the case when commercial buildings are equipped with solar photovoltaic systems. 330B Value Chain Innovations:Doing Good by Doing Well Sponsored: Manufacturing & Service Oper Mgmt Sponsored Session Chair: Ravi Anupindi, University of Michigan, Ann Arbor, MI, 48109, United States, anupindi@umich.edu 1 - Giving it Away to Increase Profits: Price Discrimination and the Effect of Free Goods Jacob Chestnut, University of Michigan, Ann Arbor, MI, United States, jacobpc@umich.edu, Ravi Anupindi, Hyun-Soo Ahn Conventional wisdom suggests that a service provider must charge a customer in some form to generate profit. However, a handful of providers do not follow this and give away services to some customers for free. Dr. Devi Shetty, called the “Henry Ford of Cardiac Surgery,” is the founder of India’s Narayana Health, which performs 40% of surgeries for free. India’s Aravind Eye Hospital (AEH) is another well-known example. Though nominally non-profit, with a net surplus of 50% while serving 60% of their consumers for free, AEH’s performance suggests that offering partially free service may be more than charity; it may actually increase a provider’s total profit. 2 - Assessing the Impact of Telemedicine-Equipped Service Channels on Patient Access Kamalini Ramdas, London Business School, London, United Kingdom, kramdas@london.edu, Sarang Deo, Kraig Delana, Ganesh Babu, Sri Harinath We use data from the Aravind Eye Care System in India to examine how the introduction of rural vision centers equipped with telemedicine impacts patient visit volumes, patient mix, revenues and outcomes. Using a difference-in- differences model, we find that the introduction of vision centers substantially increases network volumes, largely through new patients. We also find that patients switch to care closer to home when feasible. Our findings suggest that telemedicine can successfully catalyse care seeking behavior and can enable a pull model of care in rural areas. 3 - Optimal Subsidies for Solar Lanterns in Haiti Chris Tang, UCLA Anderson School, CA, United States, chris.tang@anderson.ucla.edu, ManMohan Sodhi, James Knuckles Development supply chains focus on the economic sustainability of poor families. To understand these better, we conducted a field study of such supply chains for solar lanterns in Haiti during 2014-2016. Upon interviewing donor organizations such as the World Bank, we found that the answer to which particular echelon in the supply chain should the donor subsidize differed from one donor to the other and even within donor organizations. Using stylized models, we seek to find the best way to subsidize a multi- echelon supply chain when the donor’s budget is limited. Yangfang Zhou, Singapore Management University, 50 Stamford Road, Singapore, 178899, Singapore, helenzhou@smu.edu.sg SC10

332A Data-driven Decision Making in Healthcare and Service Operations Sponsored: Manufacturing & Service Oper Mgmt, Service Operations Sponsored Session Chair: Pengyi Shi, Purdue University, West Lafayette, IN, 47907, United States, shi178@purdue.edu Chair: Nan Liu, Columbia University, Columbia University, New York, Kimia Ghobadi, MIT, 100 Main Street, E62-459, Cambridge, MA, 02142, United States, kimiag@mit.edu, Michael Hu, Retsef Levi, Adam Marshall, Wendi Rieb, Bethany Daily, Inga Lennes, John Stone, Ana Cecilia Zenteno We developed real-time (online) intra- and inter-day algorithms to schedule outpatient infusion appointments while respecting patient choices. Each appointment is scheduled upon arrival without prior knowledge of future appointments or patient preferences. The goal of the algorithms is to minimize the number of required resources. We analyze the algorithms’ performance and provide competitive ratio bounds. The algorithms are tested on two large infusion centers in an academic medical center and the results illustrate up to 34% improvement compared to the centers’ historical data. 2 - Improving the use of Operating Rooms using Surgeon Input Brian Han, Marshall School of Business, University of Southern California, Los Angeles, CA, United States, rongqing.han.2019@marshall.usc.edu, Song-Hee Kim When allocating operating room times to surgery cases, hospitals need to know how long the surgeries will take. Although the estimation of surgery case duration has been extensively studied, accurately predicting surgery case duration remains a challenge. We examine ways to systematically combine surgeons’ forecasts with a model based on observed attributes to improve the accuracy of surgery case duration predictions, and hence the use of operating rooms. 3 - Dynamic Appointment Scheduling of Elective Surgeries under Bed Capacity Constraint Chengyu Wu, Duke University, 877 Louise Circle, Durham, NC, 27705, United States, chengyu.wu@duke.edu, Li Chen, Jing-Sheng Jeannette Song We study the problem of scheduling elective surgeries that aims to provide patients with specific surgery dates at the time when they call in, taking into account the ICU capacity and occupancy. In doing so, we develop a heuristic and then validate it using real hospital data. 4 - Managing Appointment-based Services in the Presence of Walk-in Customers Nan Liu, Columbia University, New York, NY, 10032, United States, nan.liu@columbia.edu, Shan Wang, Guohua Wan Walk-in customers are accepted in many service industries and especially in healthcare. Motivated by practice in two large community health care networks in NYC, we study how to schedule patients in a clinic session in anticipation for random walk-ins. We use a Poisson regression framework to analyze the temporal pattern of walk-ins based on 3-year data, and propose data-driven optimization models to identify the optimal appointment schedule. We show that the objective function is multimodular, and this elegant structural property allows us to develop efficient solution algorithms. Our models can be applied to general appointment-based services in the presence of random walk-in customers. NY, 10032, United States, nl2320@columbia.edu 1 - Real-time Outpatient Scheduling Algorithms

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