Informs 2015

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INFORMS Philadelphia – 2015
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2 - Mining Association between Promotions and Transactions to
Find Optimum Time for Targeted Promotions
Hari Koduvely, Dr, Samsung, # 2870,Orion Building, Outer Ring
Road, Bangalore, K, 560037, India,
Roshni Mohandas
In the usual Targeted Promotion scenario one optimizes the promotion content
tailored towards a consumer’s purchase interests to maximize response. However
time of targeting a promotion also equally important. In this paper we present a
new method, based on the temporal association patterns between promotion and
transaction events, to find the optimum time for targeted promotions. We validate
our method against existing approaches on a real retail data set and show
significantly better results.
3 - The Effect of Non-local Diversity in Dynamic Class Prediction
Senay Yasar Saglam, PhD Student, University of Iowa, 108
Pappajohn Business Building, S210, Iowa City, IA, 52242, United
States of America, , Nick Street
Classifiers’ agreement in the region where a new data instance resides in has been
considered a major factor in dynamic ensembles. We hypothesize that in this
region the agreement among classifiers that are different is more important than
among the similar ones. In other words, high local accuracy and confidence, and
high diversity in other regions, is desirable. In this study, we check the validity of
this hypothesis and verify that diversity still plays a role in the dynamic class
prediction.
4 - Measuring Influence in Online Social Network Based on the
User-content Bipartite Graph
Zhiguo Zhu, Associate Prof., Dongbei University of Finance and
Economics, No. 217 JianShan St., Shahekou District, Dalian,
110625, China,
How to precisely identify and measure influence has been a hot research
direction. Differentiating from existing researches, we are devoted to combining
the status of users in the network and the contents generated from these users to
synthetically measure the influence diffusion. In this paper, we firstly proposed a
directed user-content bipartite graph model. Finally, the experiment results verify
our proposed model can discover most influential users and popular broads
effectively.
TC33
33-Room 410, Marriott
Appointment Scheduling in Healthcare
Sponsor: Health Applications
Sponsored Session
Chair: Armagan Bayram, Northwestern University, 2145 Sheridan
Road, Evanston, IL, 60201, United States of America,
1 - Ensuring Timely Access and Adequate Capacity for an
Endocrinology Clinic
Moses Chan, University of Michigan, 1205 Beal Avenue,
Ann Arbor, MI, United States of America, ,
Amy Cohn, Amy Rothberg
The weight management program was designed to promote weight loss for
morbidly obese patients. Program participation is associated with reductions in
BMI and improvements in cardiovascular risk factors and quality of life. Providers
are booked weeks out, posing a challenge to schedule consecutive weekly visits.
Non-adherence to schedule undermines the effectiveness of the program. The
purpose of this study is to improve patient compliance with the program and to
increase program access.
2 - An Online Appointment Scheduling Model
Ali Kemal Dogru, Om PhD Student, University of Alabama, 315
Bidgood Hall, 361 Stadium Drive, Tuscaloosa, AL, 35487, United
States of America, Sharif Melouk
Incorporating patient centered medical home (PCMH) principles, we develop an
online appointment scheduling system (OASS) for a primary care setting. We
propose a simulation optimization solution approach that uses two models
working in concert to provide high quality solutions (i.e., schedules) in short
time. We aim to minimize: 1) weighted cost of expected patient waiting time and
2) doctor idle time and overtime. Key Words: Online Appointment Scheduling,
Simulation Optimization, PCMH
3 - Managing Series Patients in a Healthcare Facility
Siyun Yu, STOR Department, UNC-Chapel Hill, B26 Hanes Hall,
Chapel Hill, NC, 27514, United States of America,
Vidyadhar Kulkarni, Vinayak Deshpande
Series patients are scheduled for a series of appointments, such as patients in
physical therapy clinic, dialysis center, etc. To balance the demands from different
types of new as well as returning patients and the available appointment slots, we
develop stochastic models to determine the number of slots and the scheduling
policy that optimize performance. Heuristic polices are proposed which share the
same structural properties of the optimal policy and are more computationally
efficient.
4 - Managing Virtual Appointments in Chronic Care
Armagan Bayram, Northwestern University, 2145 Sheridan Road,
Evanston, IL, 60201, United States of America,
, Seyed Iravani, Sarang Deo,
Karen Smilowitz
Virtual visits can assist in managing chronic conditions by providing low cost
monitoring, treatment and education. Motivated by these benefits, we develop
capacity allocation models that decide which patients to schedule given limited
availability of both office and virtual visit slots. We model this problem using a
dynamic programming framework over a finite horizon, and perform analytical
and numerical analyses to identify policies for scheduling patients for different
medical interventions.
TC34
34-Room 411, Marriott
Optimal Cancer Therapy
Sponsor: Health Applications
Sponsored Session
Chair: Kevin Leder, Assistant Professor, University of Minnesota,
111 Church St, Minneapolis, MN, 55455, United States of America,
1 - Nonstationary Spatiotemporally Integrated Fractionation
Ali Ajdari, University of Washington, Industrial and Systems
Engineering, Seattle, WA, 98195,
Archis Ghate
We consider the optimal fractionation problem where the fluence-maps are
allowed to change over treatment sessions. This results in a high-dimensional
nonconvex dynamic optimization problem. We present an approximate solution
method rooted in convex and dynamic programming.
2 - Treatment of Chronic Myeloid Leukemia with Multiple
Targeted Therapies
Qie He, University of Minnesota, 111 Church Street SE,
Minneapolis, MN, United States of America,
Junfeng Zhu, Kevin Leder, Jasmine Foo
Recently several targeted therapies have been developed to treat Chronic Myeloid
Leukemia (CML). A significant problem is the development of resistance to
therapy in patients. Therapy combination can slow this development, but the
number of combinations is huge. We develop a model to find combinations that
are promising for clinical trials. The model captures cell evolution and toxicity
constraints. Our optimal combinations are predicted to significantly outperform
common clinical practice.
3 - Combined Therapy in Acute Lymphoblastic Leukemia
Kevin Leder, Assistant Professor, University of Minnesota, 111
Church St, Minneapolis, MN, 55455, United States of America,
Acute lymphoblastic leukemia is a cancer of the blood system. While successful
treatment of the disease in juvenile patients is possible, it is difficult to treat in
adult patients. One treatment modality is the use of the targeted therapy nilotinib.
However, drug resistance is a serious issue. To avoid this drug resistance we
consider the combination of nilotinib and radiation. We develop a mathematical
model for this combined therapy and compare with experimental observations.
TC34