2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
168
2 - Behavioral Drivers Of Routing Decisions: Evidence From
Restaurant Table Assignment
Bradley R Staats, University of North Carolina at Chapel Hill,
Campus Box 3490, McColl 4721, Chapel Hill, NC, 27599-3490,
United States, Fangyun Tan
In many settings, humans make routing decisions dynamically, either because
algorithms don’t exist, decision support tools have not been implemented, or
existing rules are not enforced. Understanding how individuals make decisions
creates the opportunity to identify both positive deviances, as well as suboptimal
decision making that can be improved. In this paper we theoretically identify the
factors that may impact decision making before empirically examining a large
operational data set in a casual restaurant setting to research whether and how
hosts deviate from their predefined round-robin rule to seat customers to servers.
3 - The Impact Of Delay Announcements: An Experimental Approach
Gad Allon, Northwestern University, Evanston, IN, United States,
, Achal Bassamboo,
Mirko Kremer
We explore the impact of delay announcements by studying the data from a lab
experiment, where customers are provided with anticipated delay.
4 - Diagnostic Accuracy In Congested Environment
Mirko Kremer, Frankfurt School of Finance and Management
gGmbh, , Francis E DeVericourt
The trade-off between diagnostic accuracy and congestion characterizes many
manufacturing and service settings, where the gathering of additional information
is likely to improve the diagnosis but may also increase congestion in the system.
For example, medical staff often needs to weigh the benefit of running additional
tests against the cost of delaying the provision of services to other patients. We
present the results from a set of controlled laboratory experiments designed to
test the predictions of a formal sequential testing model that captures this trade-
off.
MB58
Music Row 6- Omni
Energy VI
Contributed Session
Chair: Luis Baringo, Universidad de Castilla-La Mancha, Av. Camilo
José Cela s/n, E.T.S.I.Industriales, Ciudad Real, 13071, Spain,
1 - Resilient Based Power System Restoration On Sectionalized Grid
Saeedeh Abbasi, Research and Teaching Assistant, University of
Houston, 9000 Braesmont Dr, Apt #4, Houston, TX, 77096,
United States, , Masoud Barati, Gino J Lim
Several catastrophic experiences of extreme events increased the criticality of the
power grid restoration. This paper discusses a novel resilience-based restoration
and sectionalizing model. This restoration approach aims to restore the de-
energized power grids to the normal state after cascading outages that may occur
during severe conditions. The problem is formulated as a bi-level programming
model and solved by the pre-emptive programming method. The proposed
approach is illustrated using an IEEE six-bus and 118 bus test systems, with focus
on assessing and improving its resilience during the restoration process to severe
disasters.
2 - A Generation Capacity Expansion Planning Model Considering
Capacity Markets With High Wind Power Penetrations
Jonghwan Kwon, Arizona State University, 10410 N Cave Creek
Rd, Tempe, AZ, 85020, United States, ,
Zhi Zhou, Todd Levin, Fernando de Sisternes, Kory W Hedman,
Audun Botterud
This work aims to develop a modeling framework for simulating generation
capacity expansion planning, considering long-term capacity markets and short-
term energy and operating reserve markets with increasing levels of wind power.
The framework will provide the ability to analyze the impact of high wind
penetrations on the economics and reliability of the grid in a more realistic
market environment. System operators and regulators can obtain new and
important insights into how wind resources can be efficiently and effectively
integrated into electricity markets under various rules and policies.
3 - Electricity Pooling Markets With Inelastic Demand
Mohammad Rasouli, PhD Candidate, University of Michigan,
430 S Fourth Ave, Ann Arbor, MI, 48104, United States,
, Demosthenis Teneketzis
In the restructured electricity industry, electricity pooling markets are an
oligopoly with strategic producers possessing private information. We focus on
pooling markets where aggregate demand is represented by a non-strategic agent
and is inelastic.
Inelasticity of demand is a main difficulty in electricity markets. It can potentially
result in market failure and high prices.
We propose a market mechanism that has the following features. (F1)It is
individually rational.(F2)It is budget balanced.(F3)It is price efficient(F4)The
energy production profile corresponding to every non-zero Nash equilibrium of
the game induced by the mechanism is a solution maximizes the social welfare.
4 - Offering Strategy Of A Virtual Power Plant: A Stochastic Adaptive
Robust Optimization Approach
Luis Baringo, Universidad de Castilla-La Mancha, Av. Camilo José
Cela s/n, E.T.S.I. Industriales, Ciudad Real, 13071, Spain,
Ana Baringo
We propose a stochastic adaptive robust optimization model for the offering
strategy of a virtual power plant (VPP) that participates in the day-ahead and the
real-time energy markets. The VPP comprises a conventional power plant, a
wind-power unit, a storage facility, and flexible demands, which participate in the
markets as a single entity in order to optimize their energy resources.
Uncertainties in the wind-power production and in the market prices are
modeled using confidence bounds and scenarios, respectively.
MB59
Cumberland 1- Omni
Connected and Automated Vehicles
Sponsored: Transportation Science & Logistics
Sponsored Session
Chair: Michael Levin, University of Texas, Austin, TX, United States,
1 - Modeling Spatiotemporal Propagation Of Information In a
Connected Vehicle System With The Consideration Of
Communication Capacity
Jian Wang, Purdue University, Lyles School of Civil Engineering,
West Lafayette, IN, United States,
Xiaozheng He, Yong Hoon kim, Srinivas Peeta
This study proposes integro-differential equations to model the spatiotemporal
propagation of information under vehicle-to-vehicle communications while
factoring communication capacity and traffic dynamics. We also derive closed
form solutions for the asymptotic speeds of information propagation wave under
different densities of equipped vehicles. Numerical experiments demonstrate the
effectiveness of the proposed model in various traffic conditions.
2 - Road In Transition: Autonomous Vehicle Manufacturer Strategies
And Transportation Systems Performance
Mohamadhossein Noruzoliaee, University of Illinois at Chicago,
Chicago, IL, United States, , Bo Zou,
Yang Liu
This study explores the impacts of autonomous vehicles (AVs) on transportation
system equilibrium and AV manufacturer pricing strategies. A mathematical
program with equilibrium constraints (MPEC) is formulated, where the upper
level determines pricing strategy of an AV manufacturer and the lower-level
computes system equilibrium as a variational inequality (VI). Besides, the
competition among multiple AV manufacturers is formulated as an equilibrium
problem with equilibrium constraints (EPEC). Solving the MPEC and EPEC helps
gauge the impact of market-driven AV pricing on system performance.
3 - A Cell Transmission Model For Dynamic Lane Reversal With
AutonomousVehicles
Michael Levin, University of Texas, Austin, TX, United States,
Autonomous vehicles admit consideration of novel traffic behaviors such as
reservation-based intersection controls and dynamic lane reversal. We present a
cell transmission model formulation for dynamic lane reversal. For deterministic
demand, we formulate the dynamic lane reversal control problem for a single link
as an integer program and derive theoretical results. In reality, demand is not
known perfectly at arbitrary times in the future. To address stochastic demand,
we present a Markov decision process formulation. Due to the large state size, the
Markov decision process is intractable. However, based on theoretical results from
the integer program, we derive an effective heuristic. We demonstrate significant
improvements over a fixed lane configuration both on a single bottleneck link
with varying demands, and on the downtown Austin network.
MB58