2016 INFORMS Annual Meeting Program

SB50

INFORMS Nashville – 2016

2 - Shipment Consolidation And Dispatching Problem At Ekol Logistics

3 - Online Overbooking Strategies In Outpatient Specialty Clinics With No-shows And Advance Cancellations Shannon Harris, Ohio State University, harris.2572@osu.edu Jerrold H May, Luis G Vargas Patient behavior, such as no-shows and cancellations, can lead to issues that heighten outpatient clinic access issues. In this paper, we develop strategies to determine if and when to overbook patients, over a finite horizon, in an online scheduling environment. We incorporate clinic parameters, no-shows, and cancellations to inform the overbooking decisions. We find that the optimal overbooking strategies are a function of both no-shows and cancellations, and that a clinic can, under certain conditions, achieve a greater service reward by overbooking patients than it can by not overbooking. Our work is motivated, in part, by our observations of scheduling at a VHA specialty clinic. 4 - Modeling For The Equitable And Effective Distribution Of Food Donations Under Stochastic Capacities Irem Sengul Orgut, Quality Analytics Project Manager, Lenovo, Raleigh, NC, United States, isengul@ncsu.edu, Julie Ivy, Reha Uzsoy Food insecurity is an increasing threat to people’s health status and quality of life. In partnership with the Food Bank of Central and Eastern North Carolina, which distributes donated food to a 34-county service area, our objective is to achieve equitable and effective food distribution among the population at risk for hunger. Counties’ capacities are the main source of uncertainty in this system as they constrain the total food distribution due to the need to distribute food equitably. We develop stochastic models for optimal food distribution and prove structural results. We illustrate our results and perform an extensive numerical study using historical data from our collaborating food bank. 213-MCC Emergency Response, Recovery, and Resilience Sponsored: Public Sector OR Sponsored Session Chair: Laura Albert McLay, University of Wisconsin-Madison, 3218 Mechanical Engineering Building, 1513 University Avenue, Madison, WI, 53706, United States, laura@engr.wisc.edu 1 - Resilience-based Component Importance Measures For Interdependent Infrastructure Networks Yasser Almoghathawi, University of Oklahoma, Norman, OK, United States, moghathawi@ou.edu Kash Barker Interdependent infrastructure networks are subjected to disruptions due to different disruptive events. Consequently, a failure in one network could lead to a failure in another network. We propose two resilience-based component importance measures to quantify the impact of the disrupted components on the resilience of the interdependent infrastructure networks and rank them according to their criticality to focus on preparedness efforts. 2 - An Integrated Network Design And Scheduling Problem For Network Recovery And Emergency Response Suzan Afacan, Graduate Student, University of Wisconsin- Madison, Madison, WI, 53705, United States, iloglu@wisc.edu, Laura Albert McLay Infrastructure recovery is important for delivering time-sensitive services and commodities after a disaster while also repairing network damage. To examine this issue, we present an extension of the p-median problem in the case of extreme events. In the model, we coordinate two types of service providers: (1) recovery crews who repair disrupted roads and (2) emergency responders who deliver services and commodities. The objective is to minimize the cumulative weighted distance between the emergency responders and the calls for service over the time horizon. We also present a new backup coverage model with the same extension. The models are illustrated with the computational examples. 3 - Dynamic Programming For Ambulance Fleet Management Amir Rastpour, Postdoctoral Fellow, University of Western Ontario, Ivey Business School, 1255 Western Road,, London, ON, N6G0N1, Canada, arastpour@ivey.uwo.ca, Mehmet A. Begen, Armann Ingolfsson, Greg Zaric We use dynamic programming to model ambulance systems. Our model can potentially assist ambulance dispatchers to proactively take actions to avoid high operational costs, lost calls, and the proportions of urgent calls that are not covered timely, or a weighted sum of these performance measures. Possible actions that we consider are: Calling in additional ambulances from neighboring cities, expediting the service, and repositioning available ambulances following a desired compliance table. We use a detailed simulation model to validate our results. SB51

Sinem Tokcaer, zmir University of Economics, Izmir, Turkey, sinem.tokcaer@ieu.edu.tr, Ozgur Ozpeynirci, Muhittin H. Demir, Irem Celik The case considers international freight forwarding operations in Ekol Logistics of Turkey; a leading international logistics company. Less-than-truckload orders are routed either directly to destination, or through a cross dock. Currently, the consolidation and dispatching plan is done manually. The case has two phases: first, students analyze the cost structure to determine the total cost for a given plan and suggest a better one. The second phase involves the construction of the mathematical programming formulation to identify an optimal plan. Students are also required to identify alternative feasible routes to be fed into the formulation, in search for an improved optimal plan. 3 - Inventory Optimization For Rent The Runway Vincent Slaugh, Cornell University, Ithaca, NY, United States, vslaugh@cornell.edu, Sridhar Tayur The choice of how many rental dresses to procure in advance of each fashion season plays a critical role in the success of Rent the Runway, an online high- fashion dress rental business. The case leads students through this inventory optimization decision for a single dress style using both queueing and Monte Carlo simulation models implemented in a spreadsheet. Students are encouraged to consider the strengths and weaknesses of each modeling approach and how to incorporate additional model features such as nonstationary demand and the random loss of rental units. 4 - The Safe Birth Clinic Milind Dawande, The University of Texas at Dallas, Richardson, TX, United States, milind@utdallas.edu, Tim Huh, Ganesh Janakiraman, Mahesh Nagarajan, Yang Bo The effective utilization of capacity is an important operational goal that managers strive to achieve. Most textbooks use the following simple “bottleneck formula” to calculate process capacity: the capacity of each resource is first calculated by examining that resource in isolation; process capacity is then taken as the smallest (bottleneck) among the capacities of the resources. The main goal of this case is to alert students that, for processes in which activities share resources, the use of the bottleneck formula brings the potential danger of reaching incorrect conclusions about process capacity and may eventually lead to erroneous decisions with significant financial impact. Chair: Shannon Harris, Ohio State University, 600 Fisher Hall, Columbus, OH, 43210, United States, harris.2572@osu.edu 1 - Simulation Optimization To Inform Decision Making In Birth Karen T Hicklin, University of North Carolina, Chapel Hill, NC, United States, kthickli@ncsu.edu, Julie Ivy Of the nearly 4 million births that occur each year in the U.S., almost 1 in 3 is a cesarean section (C-section). Due to the various increased risks associated with C- sections and the potential major complications in subsequent pregnancies, a re-evaluation of the C-section rate has been a topic of major concern. We present a discrete event simulation model of women undergoing a trial of labor with the goals to: (1) model the natural progression of labor for spontaneous and induced laboring patients and (2) optimally decide when an intervention is needed, such as augmentation or C-section, in order to reduce the number of C-sections due to a “failure-to-progress” diagnosis. 2 - Dynamic Control Of A Single Server System When Jobs Change Status Gabriel Zayas-Caban, University of Michigan, gzayasca@umich.edu Many systems must contend with allocating resources to jobs whose initial service requirements or costs change when they wait too long. We present a new queueing model for this scenario and use a Markov decision process formulation to analyze assignment policies that minimize holding costs. We provide sufficient conditions under which simple priority rules hold and for when switching curve structures hold. In general, we find that allowing service and/or cost requirements to change changes the structure of optimal controls for resource allocation in queueing systems. SB50 212-MCC Decision Making in Healthcare Sponsored: Minority Issues Sponsored Session

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