Informs Annual Meeting 2017

TD50

INFORMS Houston – 2017

TD50

2 - Bioenergy Facility Location: A Dynamic Problem to Address Electricity Demand and Supply Gap Raza Ali Rafique, Assistant Professor, Lahore University of Management Sciences (LUMS), Sector ‘U’, DHA, Lahore Cantt., Lahore, 54792, Pakistan, raza.ali@lums.edu.pk, Mohsin Nasir Jat In this research, the optimal locations of bioenergy facilities are sought. We propose a mixed integer linear programming (MILP) approach for minimization of energy gap (between demand and supply) at district levels with defined biofuel potential and targeted electricity capacity. Our study is based on real data collected across 135 districts of Pakistan. The proposed optimization tool can assist policy makers for strategic planning and development of biofuel energy in Pakistan. 3 - Planning for Electric Taxi Charging System from the Perspective of Transport Energy Supply Chain- A Data Driven Approach Yinghao Jia, PhD Candidate, Tsinghua University, Beijing, 100084, China, jyh12369@126.com Yinghao Jia, PhD Candidate, Sparkzone Research Group, Beijing, China, jyh12369@126.com, Ziyang Guo, Zhuying Jiang, Yu Xin, Yide Zhao, Fang He Administration in big cities is strongly promoting electric taxis (ETs) by providing purchasing subsidies, public charging facilities and many other encouraging policies. However, how to allocate the limited resources to optimize the benefits brought by ETs remains a headache for most researchers. Applying data mining technology, this research gathers real-time vehicle trajectory data of 39,053 urban conventional taxis (CTs) and 408 suburban ETs in Beijing for 4 weeks to extract the model of customers’ travel demand and ET driving patterns. Based on the transport energy supply chain derived from GPS data, we develop a data-driven method to design ET charging infrastructure in the near future. 4 - Storage Dam and RUF off River Hydroelectric Power Generation and Distribution Planning We present power delivery planning problem for integrated storage dam and run- off-river (ROR) hydroelectric power plant projects under supply uncertainties. We formulate the problem as a two-stage stochastic program, where the storage dam projects are considered as a first stage, the ROR projects are considered as the second stage of the program. Numerical comparisons of stochastic solution, expected value solution, and wait and see solution are made to provide the economic dispatch of generators and optimal delivery plan that the power system operators can use to coordinate, control, and monitor the hydroelectric power generation and distribution system. 5 - Bus Ranking Method for Robust Optimization Amandeep Gupta, Cornell University, 316 Highland Road, Ithaca, NY, 14850, United States, ag729@cornell.edu, Lindsay Anderson Interest in efficient and flexible stochastic methods for unit commitment has been growing steadily in answer to increasing renewable energy resources on the grid. This work describes a statistical bus ranking methodology that identifies the most critical buses based on criteria such as economic dispatch cost, or ramping needs to provide a robust unit commitment solution. The method is illustrated via a case study on the IEEE 30-bus system and compared to other established approaches to demonstrate the efficacy of obtained solutions. Results show that the bus ranking method performs as well as the best of these methods, with the provision of additional flexibility and potential for parallelization. Govind Joshi, Colorado School of Mines, Golden, CO, United States, gobndjoshi@gmail.com, Ebisa Wollega

361C Fleet and Marketplace Optimization for Mobility-on- Demand (MoD) Systems with Ridepooling Sponsored: TSL, Urban Transportation Sponsored Session Chair: Samitha Samaranayake, Cornell University, Ithaca, NY, 14853, United States, samitha@alum.mit.edu 1 - Large-scale On-demand Micro-transit and Integration with Mass-transit Systems Samitha Samaranayake, Cornell University, School of Civil & Environmental Engineering, 220 Hollister Hall, Ithaca, NY, 14853, United States, samitha@alum.mit.edu This presentation will discuss two approaches for improving the scalability of on- demand ridesharing systems. The first approach is a micro-transit system that serves passenger demand using a fleet of high capacity shuttles, while still assigning passengers to vehicles and routing vehicles in real-time. A novel solution framework is used to solve the problem at scale. The second approach considers integrating on-demand ridesharing with mass-transit. Large-scale simulations of both approaches, using real taxi trip data from NYC, demonstrate the efficiency gains made possible by these systems. 2 - Pricing and Optimization in Shared Vehicle Systems Siddhartha Banerjee, Cornell University, 229 Rhodes Hall, Ithaca, NY, 14853, United States, sbanerjee@cornell.edu, Daniel Freund, Thodoris Lykouris We develop a framework for optimizing shared-vehicle systems, modeled using closed queueing networks. Our approach gives the first efficient algorithms with rigorous guarantees for several common demand-supply balancing controls, including pricing, rebalancing and matching, in the process simplifying and extending several recent results. Moreover, our framework, which is based on a novel convex relaxation coupled with a new infinite-projection and pullback technique, may prove useful for proving approximation bounds in other settings. 3 - Estimating Willingness to Carpool at Uber Peter Frazier, Cornell University, School of Operations Research, and Information Engineering, Ithaca, NY, 14853, United States, pf98@cornell.edu We consider estimation of a rider’s willingness to use rideshare-based carpooling as a function of inconvenience created by carpooling, price of the carpool product, and the price of a non-carpool alternative. Such estimates are critical for pricing rideshare based-carpooling, and for designing the matching algorithm and constraints that determine inconvenience. We present estimation methodology and insights from applying this methodology at Uber. 4 - Enhancing Urban Mobility: Integrating Ride-sharing and Public Transit Niels Agatz, Erasmus University, Rotterdam School of Management, Burg. Oudlaan 50, Rotterdam, Netherlands, nagatz@rsm.nl, Mitja Stiglic, Martin W. P.Savelsbergh Seamless integration of ride-sharing and public transit may offer fast, reliable, and affordable transfer to and from transit stations in suburban areas thereby enhancing mobility of residents. We investigate the potential benefits of such a system, as well as the ride-matching technology required to support it, by means of an extensive computational study. Our study shows that the integration of a ride-sharing system and a public transit system can significantly enhance mobility and increase the use of public transport. 361E Energy Contributed Session Chair: Amandeep Gupta, Cornell University, Ithaca, NY, United States, ag729@cornell.edu 1 - A Building Thermal Model for Humidity Prediction Jingyang Xu, Innovative Decisions & Analytics LLC, 6991 Brescia Way, Orlando, FL, 32819, United States, jxu7@buffalo.edu, Daniel Nikolaev Nikovski In this talk, we’ll show you a grey-box model to predict temperature and humidity in a building with active control of HVAC (heating, ventilation and air conditioning) systems. Various factors are considered, such as weather, human activity, radiation, moisture absorption/desorption, ventilation, condensation, etc. Accurate prediction results are obtained using data collected from a physical building. The prediction time step is 5 mins, which is much short than existing models and made it possible for the model to support optimal control of HVAC for better thermal comfort and energy consumption. TD52

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361F Hazardous Materials Transportation Invited: TSL, Intelligent Transportation Systems (ITS) Invited Session

Chair: Pirmin Fontaine, Technical University of Munich, Arcisstrasse 21, LST Minner, Munich, 80333, Germany, pirmin.fontaine@tum.de 1 - Simulation and Analyzing the Hazardous Materials Transportation Interdependent Network Peng Hu, Southwest Jiaotong University, Erhuanlu Beiyiduan No. 111, Chengdu, 610031, China, hupengbaby@163.com, Bin Shuai, Zhenyao Wu Hazardous Materials Transportation Network has very tightly coupling with Traffic Flow Network of Hazmat Transportation. We build the interdependent system for the two networks. We build the interdependent system and analyze it through simulation method for knowing the robustness of the interdependent transportation network.

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