2016 INFORMS Annual Meeting Program

MA59

INFORMS Nashville – 2016

5 - Stochastic Models To Optimize Biomanufacturing Operations Tugce Martagan, Eindhoven University of Technology, School of Industrial Engineering, Eindhoven, Netherlands, t.g.martagan@tue.nl An interdisciplinary framework is developed to reduce costs and lead times in biomanufacturing operations. The proposed framework consists of Markov decision models that dynamically control and optimize the fermentation and purification operations. We characterize the structural properties of the optimal operating policies, and propose a new zone-based decision making approach to quantify the risks and costs in biomanufacturing operations. We provide guidelines that are easy to implement in practice, and develop approximation procedures to solve industry size problems.

5 - Multiple UAV Assisted Power Network Damage Assessment Jaeyoung Cho, Assistant Professor, Lamar University, 6195 N Major Dr., Beaumont, TX, 77713, United States, jcho@lamar.edu Gino J Lim, Seonjin Kim We presents a two-phase mathematical framework for efficient power network damage assessment using unmanned aerial vehicle (UAV). In the first phase, a two-stage stochastic integer programming optimization model is presented for damage assessment in which the first stage determines the optimal UAV locations anticipating an arrival of an extreme event, and the second stage is to adjust the UAV locations, if necessary, when the arrival time of the predicted extreme event becomes closer with updated information. UAV paths to scan the power network are generated in the second phase while minimizing operating costs of the UAVs. MA59 Cumberland 1- Omni Network Design and Operations Sponsored: Transportation Science & Logistics Sponsored Session Chair: Ali Asadabadi, George Mason University, College Park, College Park, MD, 20783, United States, ali.asadabadi@gmail.com 1 - The High Speed Train Timetable Planning Problem For The Chinese Railways Paolo Toth, University of Bologna, Bologna, Italy, paolo.toth@unibo.it We consider the Train Timetabling Problem (TTP) for the planning of high-speed trains on the Beijing-Shanghai line. We are given a set of feasible timetables for the trains already planned along the line, and the main goal consists of scheduling as many additional trains as possible. We are allowed to modify the timetables of the trains, even by changing their stopping patterns, i.e. by removing some stops. A second objective is to obtain a regular schedule with respect to stopping patterns. We propose an Integer Linear Programming Model and a heuristic algorithm. Extensive computational experiments on real-world instances of the Chinese Railways are reported. 2 - Optimal Transportation And Shoreline Infrastructure Investment Planning Under Stochastic Climate Future Ali Asadabadi, George Mason University - Fairfax, Fairfax, VA, 22030, United States, ali.asadabadi@gmail.com, Elise D Miller-Hooks The problem of optimal long-term transportation investment to protect from and mitigate against the impacts of climate change is modeled as a multi-stage, stochastic, bi-level, mixed-integer program. A recursive noisy genetic algorithm is presented to address large-scale applications. It is demonstrated on a Washington, D.C. Greater Metropolitan area case study. 3 - Global Optimization Solution Methods For Transportation Network Design Problems David Z.W. Wang, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore, wangzhiweiI@ntu.edu.sg Transportation network design problems (NDP), which determine the optimal road expansion and addition plan with assumption of various user equilibrium principles, are conventionally modelled into a bilevel programming or MPEC. The NDPs are typically nonlinear and nonconvex. We develop global optimization solution methods, applying various linearization and relaxation techniques, to obtain the global optimal solution to the NDPs. Both continuous and discrete NDPs are considered, while typical user equilibrium principles including deterministic user equilibrium and stochastic user equilibrium will be employed. 4 - Optimal Layout Of Transshipment Facilities Under Traffic Equilibrium In A Continuous Space

MA58 Music Row 6- Omni Energy V Contributed Session

Chair: Jaeyoung Cho, Assistant Professor, Lamar University, 6195 N Major Dr., Beaumont, TX, 77713, United States, jcho@lamar.edu 1 - A New Computational Method For Rolling-horizon Stochastic Optimization In Power Systems Site Wang, Clemson University, Freeman Hall, Fernow Street, Clemson, SC, 20634, United States, sitew@clemson.edu Harsha Gangammanavar, Sandra D Eksioglu, Scott J. Mason We investigate a multi-period, economic dispatch problem in a power system with high penetration of renewable resources. We propose a rolling horizon stochastic programming framework to analyze this problem. We solve this problem over a one-day horizon with sub-hourly intervals using novel warm-up techniques developed for the stochastic decomposition algorithm. We compare our stochastic approach with existing deterministic methods via extensive computational studies on real-scale systems. 2 - Greening The Vehicle Fleet: Evidence From Norway’s Co2 Feebate Shiyu Yan, Norwegian School of Economics, Bergen, Norway, shiyu.yan@nhh.no To improve vehicle fuel efficiency and reduce CO2 emissions, Norway linked vehicle registration taxes to CO2 intensities, later adapted into feebate. We exploit a detailed vehicle registration dataset by econometric techniques. We find that the vehicle tax contributes to a purchase shift towards low-emitting cars. The results show that 1000NOK tax increase for a vehicle is associated with a 1.13%-1.58% registrations reduction. A pattern of rising CO2 taxes across cars results in an elasticity (-0.06) of CO2 intensities with respect to CO2 prices. The estimated tax effect implies that the CO2 differentiated vehicle registration tax explains 79% of the reduction in average CO2 intensity of new cars. 3 - System Frequency Regulation In Renewable Dominated Power Systems With A Large Penetration Of Electric Vehicles Miguel Carrion, Universidad de Castilla-La Mancha, Avda Carlos III s/n, Toledo, Spain, miguel.carrion@uclm.es, Rafael Zárate-Miñano Future power systems based on intermittent and asynchronous units may favor frequency fluctuations owing to a) a high presence of generating units with volatile power output, b) a reduction in the number of units participating in the frequency regulation and c) a reduction in the kinetic energy stored in the rotating parts of the system. In this context, we analyze the impact of using plug- in electric vehicles to provide frequency regulation in renewable-dominated power systems. This problem is formulated as a stochastic unit commitment that takes into account the uncertainty of renewable resources and frequency regulation capabilities. The proposed formulation is tested in a realistic case study. 4 - Developing A Decision Support Tool For Expanding Waste-to- Energy Technology Within The Department Of Defense Adam Haag, Lieutenant, Student, Naval Postgraduate School, Naval Postgraduate School, 1 University Circle, Monterey, CA, 93943, United States, achaag@nps.edu This study seeks to improve the the DOD’s existing decision support tool with an additional module, which may increase the diversity and breadth of Waste-to- Energy technology within the DoD.

Zhaodong Wang, University of Illinois, Wright Street, Urbana, IL, 61801, United States, zwang137@illinois.edu Yanfeng Ouyang

This talk focuses on generalizing the location-routing problem into one that considers traffic congestion and equilibrium in a continuous space. We present a new proof that a regular hexagon shape is optimal for facility service regions under congestion. Numerical experiments are implemented to verify the correctness of our analytical solution and theoretical results are used as a building block to develop approximate solutions to more general heterogeneous cases.

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