Informs Annual Meeting Phoenix 2018

INFORMS Phoenix – 2018

TB79

2 - Deviation Distance and Sufficient Density of Alternative Fuel Stations Masashi Miyagawa, University of Yamanashi, 4-4-37, Takeda, Kofu, 400-8510, Japan This paper presents a model for determining the sufficient density of alternative fuel stations. To incorporate both flow demand and the deviation distance, the service level is represented as the probability that the vehicle can make the repeated round trip between randomly selected origin and destination within a specified deviation distance. The density of stations required to achieve a certain level of service is obtained for three cases of the refueling availability at origin and destination. The result shows how the deviation distance, the vehicle range, the trip length, and the refueling availability at origin and destination affect the sufficient density of stations. 3 - Routing Management Strategy for New Collaborative Platform for Japanese Municipalities Tsuyoshi Nobata, Tokyo University of Tokyo, Ce-408, 4-6-1, Komaba, Tokyo, Japan, Shuto Tsuchiya, Yudai Honma New collaborative platform for Japanese municipalities has been developed to integrate both the worker’s and citizen’s knowledge. As one of the functions in the platform, optimal schedule management tool has been implemented. In this presentation, we discuss the optimal routing strategies to determine day tour routes for multiple maintenance vehicles. The formulation is based on multiple traveling salesmen problems, so has high similarities with AFV routing behaviors. 4 - An Exact Solution to Profit Maximizing Electric Vehicle Routing Problem Isil Koyuncu, The University of Alabama, Tuscaioosa, AL, 35406, United States, Mesut Yavuz This talk presents a maximum profit mixed fleet electric vehicle routing problem. A mixed fleet consists of traditional gasoline or diesel and electric vehicles. Electric vehicles enable the fleet operator to reduce their operating costs as well as carbon emissions. In addition, a set of customers are willing to pay a premium to receive service by electric vehicles to reduce their supply chain carbon footprint. We formulate the emerging problem as a mixed integer linear program and present an exact solution methodology as well as their computational evaluation from our preliminary experiment. n TB79 Hyatt, Curtis A Supply Chain Management III Contributed Session Chair: Sima Sabahi, North Carolina A&T State University, 704-1C Granite Street, Greensboro, NC, 27403, United States 1 - Multi-product Supply Network with an Intermediary Omkar D. Palsule-Desai, Faculty, Indian Institute of Management Indore, Indore, 453331, India We develop game theoretic models to characterize equilibrium outcomes for competing firms in a decentralized network setting with diverse objectives. We examine implications for maintaining private products while supplying a shared product in a geographically segregated market. The firms respond to both horizontal and vertical competition in the network. Our significant contribution to the existing literature is in showing that a supply network of competing firms can survive under certain situations with the firms simultaneously supplying to their private products along with the shared product of the network. 2 - Negotiation under Competition Comparison between Nash and Kalai Smorodinsky Bargaining Framework We study the difference between the Kalai-Smorodinsky (KS) and Nash Bargaining (NB) framework in a two-tier supply chain. We find that the KS solution can lead to a more reliable negotiation outcome when contingency terms are imposed, compared to the NB solution. 3 - Investigating the Relationship Between Supply Chain Resilience and Innovation Through Fuzzy Cognitive Mapping Sima Sabahi, PhD Candidate, North Carolina A&T State University, 1601 East Market St., Greensboro, NC, 27411, United States, Paul M. Stanfield In today’s turbulent environment, an understanding of how firms can manage supply chain disruptions and improve their resiliency has become a critical subject. One of the capabilities enabling companies to overcome disruptions, and adapt to rapid changes in the environment is allocating priority and resources to innovation. Although innovation has been viewed as a key component of a firm’s long-term survival and development, the impact of innovation in improving resiliency in supply chain has been relatively disregarded. This study provides a flexible, quantitative model of the causal relationship between supply chain resilience and innovation capability through fuzzy cognitive mapping. Yuanchen Li, Purdue University, 2192 Tortuga Lane, West Lafayette, IN, 47906, United States, Qi Feng, J. George Shanthikumar

n TB77 West Bldg 213A

Emergency Response II Sponsored: Public Sector OR Sponsored Session Chair: Forough Enayaty Ahangar, University of Wisconsin-Madison, Madison, WI, 53706, United States Co-Chair: Laura Albert, University of Wisconsin-Madison, Industrial & Systems Engineering, 1513 University Avenue, Madison, WI, 53706, United States 1 - Improving the Resiliency of a State Trauma System Eric DuBois, University of Wisconsin-Madison, Industrial & Systems Engineering, 1513 University Avenue, Madison, WI, 53706, United States, Benjamin Morris, Laura Albert On average, rural trauma patients can currently expect longer average pre- hospital times and worse outcomes compared to their urban counterparts. In addition, rural responders are more easily overwhelmed by surges in demand. To address these concerns, we develop a stochastic capacitated coverage model to examine where to deploy and upgrade resources with a goal of decreasing pre- hospital times, providing greater access to high-level trauma care, and ensuring adequate backup coverage in the event of mass-casualty incidents. Computational examples drawn from motor vehicle crash data are used to demonstrate the model. 2 - Maximal Multiple Coverage and Network Restoration Problem for Disaster Recovery Suzan Iloglu, Graduate Student, University of Wisconsin-Madison, 1611 Monroe St Apt 410, Madison, WI, 53711, United States Repairing network damage in road infrastructure is important for enabling the delivery of time-sensitive response services after a disaster. To address this issue, we present an extension of the maximal multiple coverage problem that coordinates the services of network recovery crews and emergency responders. The proposed model is composed of three components: (1) network restoration, (2) relocation of emergency responders with restricted access and 3) coverage of emergency demand. The objective maximizes the coverage of emergency demand over the time horizon. Two different heuristics are presented to construct high quality feasible solutions to the problem and tested using real world data. 3 - Modeling and Analysis in Tele-ICU Setting: Intervention with Preemptive Priorities Xuanjing Li, Tsinghua University, Room 519, ShunDe, Beijing, China, Xiaolei Xie, Muer Yang, Michael Fry, Dacheng Liu, Corey Scurlock Tele-ICU is a novel approach to provide critical care remotely along with the bedside ICU team. We investigate optimal staff capacity and scheduling policies using both analytical and simulation models based on a real case. We also provide managerial insights regarding dedicated staff and flexible staff in the Tele-ICU. n TB78 West Bldg 213B Alternative-Fuel Vehicles Refueling and Routing Problems I Sponsored: Location Analysis Sponsored Session Chair: Ismail Capar, Texas A&M University, College Station, TX, 77843-3367, United States Co-Chair: Yudai Honma, The University of Tokyo, Tokyo, 153-8505, Japan 1 - Bender Decomposition for Large-scale Flow-refueling Location Model Ibrahim Capar, Bowling Green State University, Department of ASOR, 355 Business Administration Building, Bowling Green, OH, 43403, United States, Ismail Capar In this research, we propose a Bender Decomposition formulation to solve flow- refueling location model for alternative fuel vehicles. We improve the standard formulation through a multi-cut reformulation that uses a path based clustering to accelerate its convergence. We discuss the performance of the method in detail and share the results from extended numerical experiments.

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