Informs 2015

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INFORMS Philadelphia – 2015
323
TC15
15-Franklin 5, Marriott
Optimization Models in Radiotherapy Treatment
Planning
Sponsor: Optimization in Healthcare
Sponsored Session
Chair: Victor Wu, PhD Student, University of Michigan,
1205 Beal Avenue, Ann Arbor, MI, 48109, United States of America,
1 - Tractable Approaches to Multiple-needle Radiofrequency Ablation
Shefali Kulkarni-thaker, Graduate Student, University of Toronto,
5 Kings College Road, Medical Operations Research Lab (RS304),
Toronto, ON, (416) 978, Canada, ,
Dionne Aleman, Aaron Fenster
In radiofrequency ablation (RFA), needles are used to apply extreme heat to
tumors, eradicating cancerous cells. To optimize multiple-needle RFA treatments,
we first obtain needle trajectories and positions using minimum volume covering
sphere and ellipse formulations. Then, we optimize the heat delivery duration for
each needle using tractable approximations to several thermal damage models.
We discuss resulting clinical treatment quality for four 3D patient models.
2 - Robotic Path Finding Techniques in Stereotactic Radiosurgery
Treatment Optimization
Marlee Vandewouw, University of Toronto, 5 King’s College
Road, Toronto, Canada, ,
Kimia Ghobadi, Dionne Aleman, David Jaffray
We investigate applying robotic path finding techniques to develop treatment
plans for Gamma Knife Perfexion where the radiation is delivered continuously.
We explore the use of simultaneous localization and mapping, combined with
heuristic exploration techniques, to generate a path. A mixed integer model is
then used to find the beam times for this selected path. We discuss the advantages
and challenges of this method in comparison to the conventional forward and
inverse step-and-shoot plans.
3 - Adaptive and Robust Radiation Therapy in the Presence of Drift
Philip Allen Mar, Dept. of MIE, University of Toronto,
5 King’s College Road, Toronto, ON, M5S 3G8, Canada,
Timothy Chan
We present our computational study of an adaptive and robust optimization
radiation therapy (ARRT) method. Previously, it was shown that this ARRT
method provides asymptotically optimal treatment plans for convergent
sequences of tumor motion distributions. In this work, we generate simulated
sequences of tumor motion distributions that exhibit baseline, amplitude and
breathing phase drift, and show the effectiveness of the ARRT method applied to
these sequences.
4 - Vmat Radiation Therapy: Modeling Treatment Delivery Time
Versus Plan Quality
David Craft, Massachusetts General Hospital, 30 Fruit St, Boston,
MA, 02114, United States of America, ,
Marleen Balvert
Volumetric modulated arc therapy is a radiation method where the gantry
delivers dose continuously as it rotates around the patient. Metal leaves sweep
across the field to modulate the intensity fields. In commercial software, leaf
trajectories are solved by heuristics without any guarantee of an optimality gap.
VMAT is a large scale non-convex optimization problem with many local minima.
We offer a solution approach and explore the tradeoff between treatment quality
and delivery time.
TC16
16-Franklin 6, Marriott
Game Theory I
Contributed Session
Chair: Sam Ganzfried, Carnegie Mellon University, Computer Science
Department, 5000 Forbes Avenue, Pittsburgh, PA, 15213, United States
of America,
1 - A Stochastic Approach for Dynamic Urban Supply
Chain Management
Afrooz Ansaripour, Pennsylvania State University, 244 Leonhard
building, State College, PA, United States of America,
, Wenjing Song,
Terry Friesz, Yiou Wang, Zhaohu Fan
Lack of information sharing causes negative impacts such as traffic and pollution.
City logistics aims to optimize urban freight systems. This paper is an extension of
recent stochastic vehicle routing and scheduling frameworks. These frameworks
do not necessarily account for real-time variability in traffic. This paper
incorporates uncertainty in demand and presents a real-time stochastic
production plan and scheduling framework. SDVI will be used to obtain the
equilibrium solution.
2 - A Mixed Cooperative Dual to the Nash Equilibrium
Bill Corley, Professor, The University of Texas at Arlington,
P.O. Box 19017, Arlington, TX, 76019, United States of America,
A mixed dual to the Nash equilibrium is defined for n-person games in strategic
form. This dual extends the Berge equilibrium from pure to mixed strategies so
that mutual cooperation is achieved for the expected payoffs. Conditions are
established for the existence of a dual equilibrium. However, it is shown that for
each n>2 there exists a game for which no dual equilibrium exists. This fact may
be interpreted as there are mathematical as well as sociological obstacles to
mutual cooperation.
3 - Nash’s Continuous Transformation and a Smooth Homotopy
Method for Computing Nash Equilibrium
Yabin Sun, PhD, City University of Hong Kong, R5218, Academic
Building 2, Tat Chee Avenue, Kowloon, Hong Kong, Hong Kong -
PRC, Chuangyin Dang, Yin Chen
A different procedure often results in the different selection of Nash equilibrium.
To prove the existence of Nash equilibrium, Nash defined a continuous
transformation. This paper applies Nash’s continuous transformation to develop a
smooth homotopy method by introducing just one extra variable. Starting from
any given totally mixed strategy profile, the method numerically follows a smooth
path that ends at a Nash equilibrium. Extensive numerical results show that the
method is very efficient.
4 - When to Release Feedback in a Dynamic Tournament
Ruoyu Wang, PhD Candidate, Fuqua School of Business,
Duke University, 100 Fuqua Drive, Durham, NC, 27708,
United States of America, Brendan Daley
We study dynamic tournaments in which time is modeled explicitly, as opposed to
with the abstract notion of periods. By doing so, we characterize the effects of the
ex-ante-designated timing of an interim progress report. Whether a policy of
reporting increases total expected effort does not depend on the release time. We
find that total expected effort is single-peaked/single-troughed in the report’s
release time, with the peak/tough located at a time more than halfway through
the tournament.
5 - Endgame Solving in Large Imperfect-information Games
Sam Ganzfried, Carnegie Mellon University, Computer Science
Department, 5000 Forbes Avenue, Pittsburgh, PA, 15213, United
States of America, , Tuomas Sandholm
Sequential games of perfect information can be solved in linear time by a
straightforward backward induction procedure; however, this procedure does not
work in games with imperfect information since different endgames can contain
nodes that belong to the same information set and cannot be treated
independently. We present an efficient algorithm for performing endgame solving
in large imperfect-information games and demonstrate its success experimentally
in two-player no-limit Texas hold ‘em.
TC17
17-Franklin 7, Marriott
Network Analysis I
Sponsor: Optimization/Network Optimization
Sponsored Session
Chair: Alexander Veremyev, University of Florida, 1350 N Poquito
Road, Shalimar, FL, United States of America,
1 - Optimizing Network Recovery Time under Uncertainty
Juan Borrero, University of Pittsburgh, 3700 O’Hara Street,
Pittsburgh, PA, 15213, United States of America,
Pavlo Krokhmal, Oleg Prokopyev
We consider a network under attack, where its nodes can recover either on their
own, by receiving support from neighboring nodes, or by receiving support from
outside the network. A decision maker has to determine how to invest his budget
on these options in order to minimize recovery time. We propose a novel
hierarchical and stochastic model to address the issue, derive closed form
equations for the optimal resource allocation, and study its behavior as the
number of nodes grows to infinity.
TC17