2015 Informs Annual Meeting

TC17

INFORMS Philadelphia – 2015

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, vwwu@umich.edu 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, shefali@mie.utoronto.ca, 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 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 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, dcraft@alum.mit.edu, 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. Road, Toronto, Canada, marleev@mie.utoronto.ca, Kimia Ghobadi, Dionne Aleman, David Jaffray Philip Allen Mar, Dept. of MIE, University of Toronto, 5 King’s College Road, Toronto, ON, M5S 3G8, Canada, philip.mar@mail.utoronto.ca, Timothy Chan

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, corley@uta.edu 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, yabinsun-c@my.cityu.edu.hk, 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, rw120@duke.edu, 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, sam.ganzfried@gmail.com, 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, averemyev@ufl.edu 1 - Optimizing Network Recovery Time under Uncertainty Juan Borrero, University of Pittsburgh, 3700 O’Hara Street, Pittsburgh, PA, 15213, United States of America, jsb81@pitt.edu, 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.

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, sam.ganzfried@gmail.com 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, afrooz.ansaripour2000@gmail.com, 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

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