Informs Annual Meeting Phoenix 2018

INFORMS Phoenix – 2018

TD78

2 - Investigating the Alternative Fuel Vehicle Drivers’ Deviation Tolerances for Refueling at Stations Off Their Paths Okan Arslan, HEC Montreal, 5308 Ave Decelles, Montreal, QC, H3T1V8, Canada, Oya Ekin Karasan, Ali R. Mahjoub, Hande Yaman Due to the limited range of alternative fuel vehicles (AFV) and the sparsity of the available alternative refueling stations, the AFV drivers cooperatively deviate from their paths to refuel. The deviation is generally bounded by the drivers’ tolerance. Taking this behavior into account, we develop a natural model for the ‘refueling station location problem with routing’ based on the notion of length-bounded cuts. We quantify the impacts of the deviation tolerance of the drivers and the range of vehicles on the AFV use. We present insights on deviation characteristics of drivers and discuss the policy implications of our findings. 3 - New Node-based and Path-based Location Models for Urban Alternative-fuel Stations: Comparing Their Convenience and Coverage Abilities Yudai Honma, The University of Tokyo, Ce405, Komaba 4-6-1, Meguro-ku,, Tokyo, 153-8505, Japan, Michael J. Kuby Researchers have proposed many different models for optimizing the locations of alternative-fuel stations to serve new vehicle adopters conveniently. This paper aims to compare the path-based vs. node-based modeling choice as fairly as possible from the perspective of minimizing total additional travel time and feasibly covering all demands with the same number of stations. For this comparison, we introduce two new station location models that extend the Flow Capturing Location Model (FCLM) and the p-Median Problem (PMP) by including consistently defined upper limits on vehicle driving range and degree of inconvenience on refueling trips. 4 - Locating Alternative-fuel Stations for Maximizing AADT Coverage and Ensuring Sufficient Spacing: A Case Study of CNG Truck Fueling Qing Zhong, The University of Arizona, Tucson, AZ, United States, Daoqin Tong, Michael J. Kuby, Fangwu Wei, John W. Fowler, Keiron Bailey This paper introduces two new arc-based coverage models for locating alternative fuel stations. The new models use arc traffic volumes in the form of AADT data to represent the demand. We incorporate a service area radius and a fractional correction factor to discount for the need to detour to the station and to avoid double-counting of AADT. Station spacing parameters allow the user flexibility in not locating new stations too close to each other or to existing stations. Redundant coverage due to the proximity of multiple stations is also addressed. We apply the models to planning a network of CNG fueling stations for heavy- duty CNG-powered trucking in the Southwest United States. n TD79 Hyatt, Curtis A Supply Chain Management IV Contributed Session Chair: Weimar Ardila, University of South Florida, 4207 Winding Moss Trial, # 208, Tampa, FL, 33613, United States 1 - Optimal Inventory and Price Competition in a Dual-Omnichannel Market Bai Yang, PhD Student, Ajou University, San 5 Woncheon-dong, Yeongtong-gu, Suwon, 443 749, Korea, Republic of, Byeong-Yun Chang With the fast development of science and technology, many retailers nowadays are increasingly adopting an omnichannel SCM to sell their products. In this paper, we model the competitive dual-omnichannel supply chains and the optimal inventory and price decisions are obtained. 2 - Coordinating Efforts for New Product Development: A Bilevel Programming Approach Ece Zeliha Demirci, Postdoc Researcher, Eindhoven University of Technology, P. O. Box 513 5600 MB, Eindhoven, 5600MB, Netherlands, Nesim K. Erkip Integration of marketing and sales functions with research and development are seen as key success factors for new product development. Our study deals with a problem faced by a manufacturer produces and/or distributes a new product to the market. The aim of the manufacturer is to increase the sales of the product while influencing the retailer to stay in the market. We model this setting as bilevel programming and provide characterization of the optimal solution.

African truck drivers carry a high burden of HIV and are believed to significantly fuel its spread. We consider the problem to select locations for roadside healthcare facilities, so as to maximize their impact in terms of patient volume and continuity of access. We describe how we relate decisions to objectives and discuss how our model and its implementation in a decision support tool enable better location decisions. 2 - A Decision Support Tool for Strategic National Stockpile Inventory Policies Erica L. Gralla, George Washington University, Washington, DC, 20052, United States, Kiren Ajrawat, Alyson Fintzy, Jillian Miles, Chris Shaffer A decision support tool was developed to assist the Division of Strategic National Stockpile (DSNS) at the Centers for Disease Control and Prevention (CDC). The SNS is the nation’s largest inventory of medical supplies to utilize during a disaster. In the case of a large scale public health emergency, there is a need to both serve emergency demand and to minimize the time to recovery and degree of degradation for the commercial supply chain. The simple decision support tool shows how different policies, such as SNS inventory levels and commercial production capacities, affect the response. 3 - A Framework for Re-designing Access-to-medicine Supply Chains Nico Vandaele, KU Leuven, Naamsestraat 69, 0419.052.173, Leuven, 3000, Belgium, Catherine Jenny Decouttere, Stef Lemmens, Kim De Boeck, Mauro Bernuzzi, Stany Banzimana, Sherif Hassane We present a five-step approach to (re-)design a supply chain. It encompasses stakeholder analysis and system definition, key performance indicator derivation, detailed modelling, scenario generation and ranking up to final scenario choice and implementation. We apply this to the (re-)design of a vaccine supply chain in humanitarian setting where development and disaster relief are connected. We provide examples and insights from the Sub-Saharan region. 4 - The Role of Food Banks in Determining the Effectiveness of the Snap Program Luv Sharma, University of South Carolina, Columbia, SC, 29206, United States, Pelin Pekgun, Sanjay L. Ahire The Supplemental Nutrition Assistance Program (SNAP) is the largest domestic hunger program in the United States, providing assistance to 47 million individuals. In this study we look at the role of food banks in increasing the reach of the SNAP program. Specifically we look at the interactions between resources dedicated to the SNAP program and characteristics of the food bank service area in influencing SNAP reach. 5 - Modeling for the Equitable and Effective Distribution of Food Donations Under Stochastic Capacities Irem Sengul Orgut, Lenovo, 8209 Pritchett Farm Lane, Raleigh, NC, 27606, United States, Julie Simmons 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. n TD78 West Bldg 213B Joint session SOLA/TSL: Alternative-Fuel Location Decisions with Service Constraints 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 - Designing an Electric Vehicle Charging Infrastructure under Customer Service Constraints Ismail Capar, Texas A&M University, Industrial Distribution Program, Tamu 3367, College Station, TX, 77843-3367, United States, Ozgur M. Araz, Ibrahim Capar While there is an interest in applying the flow-refueling location model (FRLM) to capacitated refueling stations including electric vehicle charging stations, the existing research primarily focuses on capacity as the only additional constraint for the FRLM. In this research, we introduce another aspect of the capacity decisions, namely drivers’ perspective of minimizing mean sojourn time into FRLM and show results from extensive numerical experiments.

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