Informs 2015

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INFORMS Philadelphia – 2015
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MD29
29-Room 406, Marriott
Joint Session Analytics/CPMS: 2015 Innovative
Applications in Analytics Award Winner Reprise
Sponsor: Analytics
Sponsored Session
Chair: Pooja Dewan, BNSF Railway, Fort Worth, TX, 76092,
United States of America,
1 - Intelligent Surgical Scheduling System
Kalyan Pasupathy, Associate Professor, Mayo Clinic, 200 First
Street SW, HA 2-43, Rochester, MN, 55905, United States of
America, Narges Hosseini, Jeanne
Huddleston, Paul Huddleston, Yariv Marmor, Thomas Rohleder
Orthopedic Surgery was facing highly fluctuating utilization of their operating
rooms due to inaccurate estimation and scheduling of procedures. The existing
scheduling optimization problems in literature were insufficient with just a single
“optimal” solution. The team conducted descriptive research of clinical and
operational factors, developed predictive models for surgical durations, and a
prescriptive scheduling algorithm. Implementation results exhibit improvement in
key metrics.
MD30
30-Room 407, Marriott
Practice Presentations by INFORMS Roundtable
Companies III
Sponsor: INFORMS Practice
Sponsored Session
Chair: Stefan Karisch, Digital Aviation Optimization & Value Strategy,
Boeing Commercial Aviation Services, 55 Inverness Drive East,
Englewood, CO, 80112, United States of America,
1 - Xpress-mosel: New Modeling Features for Distributed and
Cloud Computing
Susanne Heipcke, FICO Xpress Optimization, FICO House,
Starley Way, Birmingham, B37 7GN, United Kingdom,
A major concern when deploying optimization models in distributed computing
environments are questions related to security for the transmission and storing of
data, and the protection of the model itself - we show examples how these are
adressed by the new Mosel module mmssl. We further discuss the new concept of
model annotations, metadata that can be used to configure optimization
applications, and touch on new interfaces (HTTP, XML, JSON, Hadoop, R).
2 - Solving the Airline Pilot Manpower Planning Problem.
Per Sjügren, Jeppesen systems AB, Odinsgatan 9, Gothenburg,
41311, Sweden,
The pilot manpower planning problem consists of the long term planning of
recruitment and promotion to meet the forecasted crew need. Complicating
factors are strict seniority promotion rules and limited training resources. We
further consider movable activities such as vacation and overtime distribution as
well as required recurrent training. We will present a high level description of the
mixed integer model, the heuristic solution process and successful applications.
3 - Prescriptive Analytics on the Cloud with Python
Vincent Beraudier, Architect And Program Manager, IBM ILOG
CPLEX, Porte Neuve, Bat A, 4 Av Alphonse Morel, Grasse, Al,
06130, France, ,
Philippe Couronne
Python’s scipy provides tools for large-scale predictive/ prescriptive analysis for
manipulating, cleaning, and crunching data, and publication-quality graphics. The
use of these web based tools with both state-of-the art OR solvers and cloud
computing will allow new users to enter the world of OR. Users with few
development skills can leverage state-of-the-art solvers to develop, tune and
publish their results without installing software. Come and discover those
scientific python pillars.
4 - A Mixed Interger Programming Model for Optimizing Wheel
Tru Operations for a Locomotive
Rajeev Namboothiri, GE Global Research,
John F Welch Technology Centre, Bangalore, India,
Srinivas Bollapragada,
Reejo Mathew, Mark Smith
FRA regulations mandate tolerance limits on locomotive wheel measurements for
safe locomotive operations. The wheel tru machine operator needs to decide the
amount of material to be trued from each wheel, and the wheels that need to be
replaced with inventory wheels, in order to comply with FRA regulations. In this
talk, we will present a novel MIP formulation for automating this complex
decision, which minimizes the total cost of the wheel tru operation, thereby
enhancing locomotive wheel life.
MD32
32-Room 409, Marriott
Big Biological Data: Computational and
Analytical Challenges
Cluster: Big Data Analytics in Computational Biology/Medicine
Invited Session
Chair: Jian Peng, Assistant Professor, University of Illinois, 2118 Siebel
Center, 201 N Goodwin Ave, Urbana, IL, 61801, United States of
America,
1 - Reconstruction of Species Histories using Genomic Data
Siavash Mirarab, UCSD, Jacobs Hall, EBU1, 2nd Floor, University
of California, San Diego, San Diego, CA, 92093, United States of
America, , Shamsuzzoha Bayzid,
Bastien Boussau, Tandy Warnow
Reconstructing phylogenies, trees that show evolutionary histories of species, can
be now attempted using genomic data. Building these species trees is complicated
by potential differences between evolutionary histories across the genome. In this
talk, we introduce two new methods used to infer whole-genome phylogenies of
48 birds and 103 plants. These new algorithms can analyze datasets with
thousands of genes and species with high accuracy, and can account for weak
signal across the genome.
2 - Entropy-Scaling Search of Massive Biological Data Sets
Noah Daniels, MIT, 32 Vassar St., 32G-572, Cambridge, MA,
02139, United States of America,
Recently, we have seen an exponential increase in biological data, outpacing
advances in computing power. Extracting new science from these massive
datasets requires algorithms that scale sublinearly in the size of the datasets. We
present a novel entropy-scaling data structure for similarity search. Applying this
data structure provides massive acceleration of several standard tools in three
biological domains: genomics, high-throughput drug screening, and protein
structure search.
MD33
33-Room 410, Marriott
Radiation Therapy Optimization:
Algorithms and Biological Effects
Sponsor: Health Applications
Sponsored Session
Chair: Gino Lim, Department Chair, Hari And Anjali Agrawal Faculty
Fellow, Associate Professor, University of Houston, E206, Engr. Bldg 2,
Houston, TX, 77204, United States of America,
1 - Benders Decomposition and an LP-based Heuristic for Selecting
IMRT Treatment Beam Angles
Sifeng Lin, The University of Texas at Austin, 1 University Station
C2200, Austin, TX, 78712, United States of America,
, Jonathan Bard, Gino Lim
This talk presents two Benders decomposition algorithms and a novel two-stage
integer programming-based heuristic to optimize the beam angle and fluence map
in Intensity Modulated Radiation Therapy planning. The results indicated that
implementing Benders using the lazy constraint usually led to better feasible
solutions than the traditional approach. Moreover, the LP rounding heuristic can
generate good solutions quickly, with further improvement obtained with the
local branching search.
2 - Robust Optimization for Craniospinal Irradiation using Intensity
Modulated Proton Therapy
Li Liao, Research Assistant, University of Houston,
4800 Calhoun Rd, Houston, TX, 77004, United States of America,
, Gino Lim, Xiaodong Zhang
Conventional passive scattering proton therapy (PSPT) is an extremely complex
technique for craniospinal irradiation (CSI). In this study, we proposed a robust
intensity modulated proton therapy (IMPT) for CSI. A small dose deviation can be
achieved when ±3 mm mis-alignment errors were applied on field junction for
the robust IMPT plans, whereas this index was more than 40% for PSPT plans. A
simplified dose model was introduced to predict dose deviation in different field
arrangement situation.
MD33