Informs 2015

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INFORMS Philadelphia – 2015
486
WE22
22-Franklin 12, Marriott
Stochastic Processes II
Contributed Session
Chair: Vincent Slaugh, Visiting Assistant Professor, Smeal College of
Business, Penn State University, 465 Business Bldg, University Park,
PA, 16802, United States of America,
1 - Solving Strategic Refinery Planning and Financial Risk Problems
via Pyomo
Ariel Uribe, Ecopetrol S.A., Km 7 Via Piedecuesta, Piedecuesta,
Colombia, , Wilson Briceño
In this work we reformulate the problem proposed by Bagajewicz & Lakkhanawat
(2008), in which is solved a refinery planning problem taking into account
financial risk management issues and the pricing effect on the planning decisions.
As a first step, we compare from a computational point of view the performance
of the deterministic and stochastic solutions between gams and pyomo. Finally,
we explore pyomo in a parallel environment.
2 - Valuation and Operation of Three Types of Power Plants using
Continuous Time Stochastic Control
Rune Ramsdal Ernstsen, University of Copenhagen, Finsensvej
42, , Frederiksberg, 2000, Denmark,
With the increasing focus on renewable energy in the deregulated energy
markets, it is to be expected that the energy mix will change and along with it the
dynamics of the energy prices. This will change the values of the existing and new
power plants, and thus change the investment incentives. My research is based on
valuation and operation of three different types of power plants in a new
electricity market: a renewable power plant, a conventional power plant and a
storage power plant.
3 - Reservation Admission Control in Rental Systems
Vincent Slaugh, Visiting Assistant Professor, Smeal College of
Business, Penn State University, 465 Business Bldg, University
Park, PA, 16802, United States of America,
Alan Scheller-wolf, Sridhar Tayur
Using a multiserver queueing model, we study the problem of whether a rental
firm should accept reservation requests during a rental season. We discuss
performance bounds and the structure of the optimal policy for admitting
reservations, and propose an easy-to-implement newsvendor-style heuristic for
accepting reservations. We show that the heuristic performs well in test cases, and
also observe that the system’s profit is decreasing in the reservation notice time.
WE23
23-Franklin 13, Marriott
New Directions in Applied Probability
Sponsor: Applied Probability
Sponsored Session
Chair: David Goldberg, Assistant Professor, Georgia Institute of
Technology, 755 Ferst Drive, NW, Atlanta, GA, 30332,
United States of America,
1 - Data-driven Dynamic Pricing and Inventory Control with Limited
Price Changes
Boxiao (beryl) Chen, University of Michigan-Ann Arbor, 1205
Beal Avenue, Ann Arbor, MI, 48109, United States of America,
, Xiuli Chao
We consider periodic review joint pricing and inventory control problem.
Demand is random and price sensitive, and the firm has limited prior knowledge
about its distribution. The firm learns the demand to maximize profit, but is faced
with the business constraint that prevents it from conducting extensive price
experimentations. We develop data-driven algorithms for pricing and inventory
decisions and prove they converge to the optimal decision at the fastest possible
speed.
2 - Rare Events in a Single Server Queue
Harsha Honnappa, Perdue University, West Lafayette, IN,
United States of America, Peter Glynn
We characterize the rare event paths of the workload process in a FIFO single
server queue that offers general service. The arrival times of a large, but finite,
population of jobs are modeled as ordered statistics of i.i.d. random variables. We
prove a large deviations principle (LDP) that shows that unlike a random walk,
the most likely paths to hit a high level are not linear. We also extend this analysis
to periodic traffic patterns, and develop an LDP for this setting as well.
3 - Efficient Monte Carlo Simulation using A Representation for
Viscosity Solutions of Hamilton Jacobi Equations
Pierre Nyquist, Brown University, 182 George Street, Providence,
RI, 02912, United States of America, ,
Henrik Hult, Boualem Djehiche
The design of efficient Monte Carlo methods is intimately connected to
(sub)solutions of certain Hamilton-Jacobi (HJ) equations. However, such
subsolutions can be hard to construct for a given problem. We discuss a min-max
representation for viscosity solutions of HJ equations and its applications to rare-
event simulation. To illustrate the result we focus on a specific setting: The use of
importance sampling to estimate rare-event probabilities in a Markovian intensity
model for credit risk.
WE24
24-Room 401, Marriott
Artificial Intelligence II
Contributed Session
Chair: Alexandra Diamond, Hunter College CUNY, 695 Park Avenue,
New York, NY, 10021, United States of America,
1 - Role-assignment for Game-theoretic Cooperation
Catherine Moon, Duke University, 213 Social Sciences, Box
90097, Durham, NC, 27705, United States of America,
Vincent Conitzer
In multiagent systems, a team of agents may work on multiple projects together.
Here, we focus on the game-theoretic aspect that needs to be considered: when
the agents are self-interested, careful role assignment is necessary to make
cooperation the repeated game’s equilibrium. We formalize this problem and find
an easy-to-check necessary and sufficient condition for a given role assignment to
induce cooperation. We also show that finding whether such assignment exists is
in general NP-hard.
2 - Discretization of Continuous Action Spaces in
Extensive-form Games
Christian Kroer, PhD Student, Carnegie Mellon University, 5000
Forbes Ave, Pittsburgh, PA, 15213, United States of America,
Tuomas Sandholm
Most equilibrium-finding algorithms for sequential games require discrete, finite
games, whereas applications often have continuity. Leveraging recent results on
abstraction solution quality, we develop the first framework for providing bounds
on solution quality for discretization of continuous action spaces in extensive-
form games. Based on this framework, we develop algorithms for finding
bound-minimizing abstractions under various structural assumptions.
3 - A New Fuzzy Kernel-free Support Vector Machine Model
Jian Luo, Assistant Professor, Dongbei University of Finance and
Economics, 217 Jianshan Street, Shahekou District, Dalian,
116025, China, , Zhibin Deng,
Xingkai Yang, Huixiang Su, Chang Liu
A new kernel-free fuzzy support vector machine model is proposed using the
concept of Fisher discriminant analysis and a new fuzzy membership function. A
decomposition algorithm is designed to solve this proposed model. Computational
results indicate that the proposed model outperforms well-known fuzzy support
vector machine models with kernels.
4 - Stochastic Approximation for Optimal Self-driven Sensor-guided
Rescue Robots under Uncertainty
Alexandra Diamond, Hunter College CUNY, 695 Park Avenue,
New York, NY, 10021, United States of America,
, Felisa Vazquez-abad
A robot must locate and retrieve an artifact that has a limited battery for sending
signals. We compare two scenarios. (1) All calculations are done in the cloud
using signals from the artifact to estimate position. The robot is then sent to the
rescue. (2) The robot has computational and sensing capabilities and it performs
the optimization in real time as it moves towards the object. The “risk” is
associated with the probability of missing the target by a certain amount. We
discuss convergence
WE22