Informs Annual Meeting Phoenix 2018

INFORMS Phoenix – 2018

TD32

4 - Public Transit Scheduling Under Ride-hailing Competition and Congestion Keji Wei, Dartmouth College, Thayer School of Engineering at Dartmouth, 14 Engineering Dr, Hanover, NH, 03755, United States, Vikrant Vaze, Alexandre Jacquillat Ride-hailing services are becoming increasingly popular in major urban and suburban areas across the world, raising many important questions about their overall impact on the quality of urban transportation and the potential shifting of passengers from public transit to ride-hailing. The objective of this study is to optimize urban public transit schedules while incorporating the impacts of ride- hailing. We present and solve a mixed-integer linear programming model that captures the dynamics between transit schedules, passenger choice, congestion and environmental impacts. 5 - The Logic of Matching in Ride Sharing Markets: Revenues, Service Ratings or Pick-up Times? Hai Wang, Singapore Management University, Room 5023, School of Information Systems, Singapore Management University, Singapore, 178902, Singapore, Wang Chi Cheung, Guodong Lyu, Chung-Piaw Teo We study a class of multi-period multi-objective online optimization problems, where a decision maker takes actions over time in an online fashion without being informed of future scenarios. To balance the trade-offs between different objectives, we develop an efficient online policy to derive the “compromise” solution, which minimizes the lp-distance from the attained KPIs to the utopia target. We apply the online policy in ride sharing market settings, and observe that all parties in the ride-sharing eco-system, from drivers, passengers, to the platform, are better off under our proposed online matching policy. Chair: Michael P. Johnson, University of Massachusetts-Boston, 100 Morrissey Blvd., Boston, MA, 02125-3393, United States 1 - Modeling the Role of Human Mobility on Dengue Outbreak Evolution in Sri Lanka Ying Zhang, Johns Hopkins University, Baltimore, MD, United States, Jefferson Riera, Kayla Ostrow, Sauleh Ahmad Siddiqui, Lauren Gardner Dengue is a prevalent mosquito-borne disease that infects approximately 390 million people every year globally, particularly in tropical and subtropical countries. There is a need to better understand and predict dengue outbreaks and transmission risk within a region so that vector control and surveillance resources can be optimally targeted. To address this issue, we model the spatial-temporal dynamics of dengue transmission as a function of human mobility patterns, in combination with land use and climate data for the Negombo region in Sri Lanka. We quantify the impact of mobility on disease-spread, and compare it to other standard predictors in the literature. 2 - Community-engaged Planning Support for Shrinking Cities and Blighted Communities Michael P. Johnson, University of Massachusetts Boston, Department of Public Policy & Public Aff, 100 Morrissey Boulevard, Boston, MA, 02125-3393, United States In the conversation about smart cities and big data, users have been presumed to be growing, progressive cities seeking to better-manage and better-plan innovative services, as well as tech-savvy residents who want to perform routine tasks more efficiently. Using a review of data and technology applications, research on decision modeling in shrinking cities and novel applications of spatial decision support for neighborhood redesign, I demonstrate how residents of under-developed communities use technology, digital data and decision modeling to make creative and data-informed decisions about the future of their neighborhoods. 3 - A Dynamic Policing Simulation Framework Khan Md Ariful Haque, The University of Texas at Arlington, Industrial, Manufacturing, & Systems Engr., Campus Box 19017, Arlington, TX, 76019-0017, United States, Victoria C.P. Chen Predictive policing seeks to predict crime, criminals, and victims. The focus is on prediction itself, as opposed to actions that might mitigate crime. Unfortunately, these predictions are only valid under the same conditions of data collection. Prediction-led policing is a concept that connects police actions to the reduction of criminal activity. This concept recognizes that the policing system is dynamic. For example, criminal behavior will be altered in response to specific actions. The presented framework proposes a structure to study dynamic policing strategies. A case study for the Arlington, TX Police Department is used to illustrate the framework. n TD30 North Bldg 221C Communities Towards a Smart City Emerging Topic: Smart Cities Emerging Topic Session

4 - Implementing Smart Cities Programs: Towards a New Agenda Tayo Fabusuyi, PhD, University of Michigan, Ann Arbor, MI, United States Despite the proliferation of analytics and technological deployments in the urban space, only incremental improvements in performance have been documented. I examine why this is the case and make the argument that the ill-structured nature of the issues at stake; obscure goals from multiple stakeholders and a myriad of poorly understood factors are contributing reasons. Drawing from the policy and community operations research literature, I make the case for a framework that broadens and enriches conventional approaches to capture the subtleties inherent in urban systems. I demonstrate the approach using as a case study the design and implementation of a smart parking program in a mid-size US city. n TD31 North Bldg 222A TSL Best Thesis Session Sponsored: Transportation Science & Logistics Sponsored Session Chair: Dirk C. Mattfeld, University of Braunschweig, Wirtschaftsinformatik, M hlenpfordtstr. 23, Braunschweig, 38106, Germany 1 - TSL Dissertation Prize Dirk C. Mattfeld, University of Braunschweig, Wirtschaftsinformatik, Myhlenpfordtstr. 23, Braunschweig, 38106, Germany The TSL Dissertation Prize is the oldest and most prestigious honor for doctoral dissertations in the transportation science and logistics area. The following criteria is used in judging candidate dissertations: i) Fundamental contribution and originality of the ideas or methods, ii) Practical importance or applicability in solving important real problems, and iii) Clarity and excellence of the exposition. n TD32 North Bldg 222B Vehicle Routing I Sponsored: TSL/Freight Transportation & Logistics Sponsored Session Chair: Camilo Ortiz-Astorquiza, Université de Montréal, Montreal, QC, H3E 1C6, Canada 1 - Robust Optimization of Heterogeneous Vehicle Routing Problems Under Demand Uncertainty Anirudh Subramanyam, Carnegie Mellon University, DH3122, The Heterogeneous Vehicle Routing Problem (HVRP) generalizes the classical VRP to allow multiple vehicle types, with different capacities, fixed and variable costs. In this work, we study a generic HVRP under demand uncertainty. First, we develop robust versions of classical local search moves. Specifically, we augment local search so that the generated vehicle routes remain capacity-feasible for demand realizations from any of five broad classes of uncertainty sets. The robustified local search is shown to be modular via two metaheuristic implementations. Second, we develop a new integer programming formulation to obtain lower bounds and quantify the quality of the metaheuristic solutions. 2 - The Inventory Routing Problem with Time Windows Gizem Ozbaygin, Sabanci University, Faculty of Engineering and Natural Sciences, Istanbul, 34956, Turkey, Esra Koca, Hande Yaman In this study, we consider the inventory routing problem with time windows (IRPTW), which is a variant of the vehicle routing problem with time windows involving inventory management decisions over a discrete planning horizon. More precisely, the inventory level at each retailer is managed by the vendor, who plans the distribution routes in a way that the retailers never run out of stock and are served within their specified time windows. We propose an exact solution approach for the IRPTW and report the results of our preliminary experiments. 5000 Forbes Ave., Pittsburgh, PA, 15213, United States, Panagiotis Petros Repoussis, Chrysanthos Gounaris

357