2016 INFORMS Annual Meeting Program

SC79

INFORMS Nashville – 2016

SC71 Electric- Omni Transportation, Public III Contributed Session

SC72 Bass- Omni Supply Chain Mgt III Contributed Session

Chair: Mehdi Zamanipour, University of Arizona, 7415 Seneca Ridge Dr, McLean, VA, 22102, United States, zamanipour@email.arizona.edu 1 - Developing an Integrated Approach To Optimize Vehicle And Driver Scheduling Problem With Equilibrium Constraint Bisheng He, Southwest Jiaotong University, 111#, 1st Section, Northern 2nd Ring Road, Chengdu, 610031, China, bishenghe@home.swjtu.edu.cn, Xiaobo Liu, Gongyuan Lu, Wei Xiao We optimized vehicle and driver scheduling problem considering equilibrium constraint to maintain their equal workload. An integer programming model was established and solved by integrating a heuristic algorism and a commercial solver. Comparison results indicated that this method could effectively improve the scheduling efficiency and equilibrium based on a real world case from Ji’nan Transit Company. 2 - How Tight Capacity Constraints Invoke Bounded Rationality And How To Consider Bounded Rationality In Designing Dynamic Capacitated Transit Service Network Jiangtao Liu, Arizona State University, 2026 S Hammond Drive, Apt 205, Tempe, AZ, 85282, United States, jliu215@asu.edu, Xuesong Zhou This talk will discuss how tight capacity constraints invoke bounded rationality and how to address bounded rational decision rules of travelers in a dynamic transit service network with tight capacity constraints. Within a space-time network, we propose an agent-based single-level integer linear programming model, which can be further decomposed as two efficiently solvable subproblems through Lagrangian decomposition. 3 - Study on The Taxi Fleet Of Electric Vehicles With Battery Swapping Lei Li, Zhejiang University, 866 Yuhangtang Rd, West Lake District, Hangzhou, 310058, China, lilei.simon@gmail.com, Qingwei Jin In this paper, we consider that a company is using electric vehicles with battery swapping to satisfy the urban taxi traveling demand. We construct a choice model based on the utility of the taxi drivers which reflects the adoption model of electric taxi vehicles. Based on the adoption model, the company is trying to maximize its profit based on the optimal decisions of battery capacity and service price. We set up a revenue model to find these optimal decisions and consider the impacts of technology advancements. We also extend this model to a mixed case in which the swapping stations serves both taxis and private vehicles. 4 - Pricing Analysis And Optimization Of Mobility On Demand Service Hao Zhou, Research Scientist, Ford Motor Company, 2101 Village Road, Dearborn, MI, 48124, United States, haozhou@umich.edu Mobility On Demand (MoD) is a new transportation system that allows users to make on demand ride request using devices such as smartphone or tablet. The MoD back-end service tries to dynamically schedule these requested rides to maximize ride-sharing while minimizing waiting time. This research tries to analyze 1) under what conditions such MoD system can be functioning efficiently, and 2) what would be the right pricing scheme for this kind of MoD system. 5 - An Integrated Priority Optimization And Intelligent Traffic Signal Control Model Mehdi Zamanipour, University of Arizona, 7415 Seneca Ridge Dr, McLean, VA, 22102, United States, zamanipour@email.arizona.edu, Govind Vadakpat In this research, an integrated priority and adaptive signal control model is developed that can intelligently consider connected vehicles and priority eligible vehicles at both intersection level and section level in a low connected vehicles penetration rate environment. Fundamentals of shockwave theory and queue estimation techniques are used in the mathematical model. Standard traffic control methods including coordinated-actuated operation are taken in to consideration. The study also conducts a sensitivity analysis on the Dedicated Short Range Communication (DSRC) by virtually extending the range.

Chair: Qinshen Tang, National University of Singapore, Business School, I Business Link, Singapore, Singapore, tang@u.nus.edu 1 - An Empirical Analysis Of Supply Chain Finance Adoption David Wuttke, EBS University, Burgstr. 5, Oestrich-Winkel, 65375, Germany, david.wuttke@ebs.edu, Eve Rosenzweig, H. Sebastian Heese We empirically test hypotheses derived, in part, from the literature on adoption of Supply Chain Finance (SCF) by buyers and their suppliers. We identify payment terms, payment terms extensions, and annual spend as important drivers of adoption speed. We also examine the ways in which the institutional environment of a supplier influences the speed of SCF adoption. In doing so, we provide a fairly comprehensive set of insights for buyers who seek to implement SCF with their suppliers. 2 - Models For Evaluating And Monitoring Supply Chain Network Design Efficiency Hakan Yildiz, Assistant Professor, Michigan State University, Department of Supply Chain Management, 370 N Business Complex, East Lansing, MI, 48824, United States, yildiz@broad.msu.edu, Sri Talluri, Jiho Yoon, John M Wassick In order to evaluate and monitor the real life effectiveness of a new supply chain network design, we employ a statistical control chart that monitors an integrated performance index generated from data envelopment analysis (DEA), which effectively considers multiple performance measures and the relationships between them. In addition, this methodology is used to trigger the re-evaluation of the network design. Moreover the clustering methods used can help management focus on improvement strategies and resource allocations. 3 - Supply Chain Performance With A Target Oriented Retailer Qinshen Tang, National University of Singapore, Business School, I Business Link, Singapore, Singapore, tang@u.nus.edu, Gongtao Lucy Chen, Melvyn Sim We study a supply chain with one supplier and one target-oriented retailer, who decides the order quantity to maximize his ability to reach a target profit, which is evaluated by a CVaR satisficing measure. We investigate how the retailer’s target- oriented preference affects the supply chain performance. With a linear target formation model, the supplier can significantly benefit from the retailer’s target- attaining behavior. The supply chain can also perform better with a target-oriented retailer than with a risk-neutral retailer. More interesting is, the target-oriented retailer can sometimes help the supply chain achieve the same efficiency level as in a centralized system. Chair: Hamoud Sultan Bin Obaid, PhD student, University of Oklahoma, 1027 E Brooks St., Apt E, Norman, OK, 73071, United States, hsbinobaid@gmail.com 1 - Strategic Nurse Allocation Policies For A Pediatric Intensive Care Unit Osman Tuncay Aydas, University of Wisconsin-Milwaukee, 3202 N Maryland Avenue, S466, Milwaukee, WI, 53202, United States, otaydas@uwm.edu, Anthony D. Ross, Kaan Kuzu We study integrated nurse staffing and scheduling in Pediatric Intensive Care Units. Feasible nurse schedules are generated using algorithms for the mixed- integer programming models developed in this work. Main objective is to reduce nurse staffing costs while balancing the under- and over staffing risks. We include a novel methodology for estimating nurse workloads by considering patient acuity and activity in the unit. 2 - Wait Time Announcements At Hospital Emergency Departments Marco Bijvank, University of Calgary, 2500 University Dr. NW, Calgary, AB, T2N 1N4, Canada, marco.bijvank@haskayne.ucalgary.ca, Zhankun Sun A number of Canadian hospitals have started publishing live emergency department (ED) wait times online in an effort to provide patients with expectations on how long they will have to wait to be seen for non-urgent care after initial assessment by a triage nurse. We accurately predict the state- dependent wait times at emergency departments based on a busy-period analysis for a multi-class, multi-server priority queue with delayed feedback. We illustrate the robustness and impact of the predictor on patient flow and patient care with a case study at four major hospitals in the Calgary area. SC79 Legends G- Omni Health Care, Modeling III Contributed Session

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