2016 INFORMS Annual Meeting Program

141 / 561

INFORMS Nashville – 2016
141
5 - Stochastic Models To Optimize Biomanufacturing Operations
Tugce Martagan, Eindhoven University of Technology,
School of Industrial Engineering, Eindhoven, Netherlands,
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.
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,
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,
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,
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,
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,
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.
5 - Multiple UAV Assisted Power Network Damage Assessment
Jaeyoung Cho, Assistant Professor, Lamar University, 6195 N
Major Dr., Beaumont, TX, 77713, United States,
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,
1 - The High Speed Train Timetable Planning Problem For The
Chinese Railways
Paolo Toth, University of Bologna, Bologna, Italy,
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, ,
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,
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
Zhaodong Wang, University of Illinois, Wright Street,
Urbana, IL, 61801, United States,
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.
MA59