2016 INFORMS Annual Meeting Program

WD25

INFORMS Nashville – 2016

3 - Delivering Long Term Surgical Care In Underserved Communities Ujjal Kumar Mukherjee, University of Illinois at Urbana–Champaign, Champiagn, IL, United States, ukm@illinois.edu, Emily J. Kohnke, Kingshuk K Sinha How can international NPOs enable the long-term delivery of surgical care in underserved communities? We report findings from a longitudinal field study spanning 11 years conducted at Gansu province of China. We triangulate insights from qualitative and quantitative data analyses to develop and validate an integrative framework that demonstrates how an international NPO’s efforts related to affordability, provider-awareness, and access are interdependent, and how the efforts interact and impact the volume and quality of surgeries in underserved communities. 4 - Improving Societal Outcomes In The Organ Donation Value Chain Priyank Arora, Georgia Institute of Technology, 800 W Peachtree St NW, Atlanta, GA, 30308, United States, priyank.arora@scheller.gatech.edu, Ravi Subramanian Our paper studies the operational actions of supply-side players in an organ donation value chain (ODVC), namely, the Organ Procurement Organization that coordinates organ recovery activities, and the hospital, where potential cadaveric donors arrive. The main contributions of our work are two-fold: First, while the majority of the literature focuses on the demand side of an ODVC, we develop an analytical model to study the effects of contextual parameters and decisions of the supply-side entities in an ODVC on their respective payoffs and societal outcomes. Second, we recommend Pareto-improving contracts that a social planner can use to help the ODVC achieve socially-optimal performance. 109-MCC Topics in Resident and Medical Student Scheduling Sponsored: Health Applications Sponsored Session Chair: Amy Cohn, University of Michigan, 1205 Beal Avenue, Ann Arbor, MI, 48109-2117, United States, amycohn@umich.edu 1 - Using Maximally Feasible And Minimally Infeasible Request Sets To Construct Resident Schedules Brian Lemay, University of Michigan, Ann Arbor, MI, United States, blemay@umich.edu, Amy Cohn, Marina Alex Epelman When scheduling healthcare providers, it is frequently not possible to satisfy every scheduling request. Multi-criteria objective functions provide one method for overcoming this challenge, but can result in undesirable schedules. We discuss an alternative method for resolving conflicting requests that identifies maximally feasible and minimally infeasible sets of scheduling requests by solving a sequence of optimization problems. We present results based on a resident scheduling problem at a major teaching hospital. 2 - A General Model For Medical Resident Rotation Scheduling William Pozehl, University of Michigan, pozewil@umich.edu, Amy Cohn Building annual rotation schedules for medical residents is often extremely challenging for program directors and chief residents. Scheduling requires a complex tradeoff of resident needs, service needs, and a multitude of preferences and requests. We present a general model for automatically constructing these schedules using linear programming and explore algorithms for iteratively improving the measures of schedule quality. 3 - Creating Resident Shift Schedules Under Multiple Objectives By Generating And Evaluating The Pareto Frontier Young-Chae Hong, University of Michigan, hongyc@umich.edu, Amy Cohn, Marina A Epelman Preparing a schedule for residents is a complex task, which requires considering a large number of complex rules and multiple conflicting metrics at the same time: patient safety, educational requirements, and resident satisfaction. However, it is not easy for chief residents to quantify weights to trade off metrics or to provide a single objective function. Thus, it is better to provide a set of Pareto schedules to the chief residents and make them choose the most preferable one. This research uses integer programming and a recursive algorithm for generating Pareto schedules to reduce the solution space for chief residents to review and to help elicit their preferences. WD24

4 - A Linear Programming Model For Scheduling Medical School Clinical Experiences Roshun Sankaran, University of Michigan, Ann Arbor, MI, United States, roshuns@umich.edu, Amy Cohn, Anna Munaco The University of Michigan Medical School unveiled a new curriculum in 2015 aimed at providing medical students with a sustained balance of science coursework and clinical exposure over their four years via the Initial Clinical Experience (ICE) and M4 Pilot programs. Building schedules for these programs are multi-criteria objective problems that consider constraints unique to each course. Easy-to-use scheduling tools using Open Solver were developed to create optimal group and clinic assignments for each program in order to streamline the scheduling process in the future. WD25 110A-MCC Logistics IV Contributed Session Chair: Jafar Namdar, University of Tennessee, 2109 Laurel Avenue, Knoxville, Knoxville, TN, 37916, United States, jafer.namdar@gmail.com 1 - Designing Robust Beef Supply Chain With Environment And Animal Welfare Costs: Small Or Large Slaughter Facilities Faisal M. Alkaabneh, Huaizhu Oliver Gao, Cornell University, Ithaca, NY, Contact: fma34@cornell.edu We consider the problem of designing robust beef supply chain for some regions in New York State by simulating supply and demand side shocks. We developed a Mixed Integer Programming model that decides simultaneously the assignment of beef slaughter facilities to beef feedlots, locating slaughter facilities, and rout- ing of trucks from slaughter facilities to a set of customers. The problem under consideration takes into account environmental costs and animal welfare. We show how the structure of the supply chain changes when considering environ- mental cost and animal welfare and how the promotion of small slaughter facili- ties provides more agile and robust network under different scenarios. 2 - Smart Logistic Management Mostafa Ghafoorivarzaneh, Student, University of Tennessee- Knoxville, 851 Neyland Drive, Room 511, Knoxville, TN, 37996, United States, mghafoor@utk.edu, Roshanak Akram, Rupy Sawhney In this study, a smart logistic management approach will be introduced. First a set of KPIs will be discussed for logistic management, which are mostly in tactical level of supply chain. At the second step information needed for smart logistic management will be collected and visualized automatically. In the third step a time dependent Periodic VRP will be introduced based on collected information in second step using a meta-heuristic approach. In the last section a heuristic rerouting method will be introduced based on collected information in second and third steps. 3 - A Robust Model Predictive Control Approach For Logistics Planning In Response To An Earthquake Yajie Liu, Associate Professor, National University of Defense Technology, Changsha, 410073, China, liuyajie@nudt.edu.cn, Hongtao Lei, Jianmai Shi Making transportation plans usually faces many challenges in response to earthquakes, especially when the post-disaster environment is dynamic and uncertain. This study provides a model predictive control (MPC) approach combined with robust optimization (RO) to the problem of efficiently transporting both commodities to affected areas and injured people to hospitals in post-disaster stage, in which the MPC approach is utilized to adjust to frequent updated information and RO is used to deal with uncertainties on each decision making point. At the end, a numerical example demonstrates the feasibility and effectiveness of our proposed approach. 4 - Designing A Resilient Supply Chain Network Jafar Namdar, University of Tennessee, 2109 Laurel Avenue, Knoxville, Knoxville, TN, 37916, United States, jafer.namdar@gmail.com, Rapinder Sawhney, Nooshin Hamidian This paper investigates different sourcing strategies to achieve supply chain resilience under disruptions aiming for a deeper understanding of how supply chain characteristics are related to resilience and how to better support disruption planning and mitigation. Specifically, we consider different coping strategies, including a single sourcing versus multiple sourcing, signing contract with backup supplier, spot purchasing, collaboration and visibility.

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