Informs 2015

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INFORMS Philadelphia – 2015
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SA31
2 - Inapproximability of Truthful Mechanisms via Generalizations of
the VC Dimension
Gal Shahaf, PhD Candidate, Hebrew University, Nataf 63, Nataf,
9080400, Israel, , Amit Daniely,
Michael Schapira
Algorithmic mechanism design (AMD) studies the delicate interplay between
computational efficiency, truthfulness, and optimality. We focus on AMD’s
paradigmatic problem: combinatorial auctions, and present new inapproximability
results for truthful mechanisms in this scenario. Our main technique is a
generalization of the classical VC dimension and the corresponding Sauer-Shelah
Lemma. Joint work with Amit Daniely and Michael Schapira
3 - Efficient Procurement Auctions with Increasing Returns
Lawrence Ausubel, Professor of Economics, University of
Maryland, Department of Economics, College Park, MD, 20742-
7211, United States of America,
Christina Aperjis, Oleg Baranov, Thayer Morrill
For procuring from sellers with decreasing returns (or selling to buyers with
diminishing marginal values), there are known efficient dynamic auction formats.
In this paper, we report progress in designing an efficient dynamic procurement
auction for the case where bidders have increasing returns. The auctioneer names
a price, and bidders report the minimum and maximum quantities that they
would sell at that price. The process repeats with lower prices, until the efficient
outcome is discovered.
4 - Competing Combinatorial Auctions
Marion Ott, RWTH Aachen University, Templergraben 64,
Aachen, 52062, Germany,
Thomas Kittsteiner, Richard Steinberg
What is the benefit of an auction format that allows for package bids for a seller
who wants to sell a set of distinct items? We show that the answer depends on
whether a seller faces competition from another seller. For a simple, tractable
model we give conditions under which a seller with the choice between VCG
mechanisms with or without package bidding prefers to disallow package bidding
if another seller with the same options is present.
SA29
29-Room 406, Marriott
Analytics
Sponsor: Analytics
Sponsored Session
Chair: Harrison Schramm, Navy Headquarters Staff, 1507 22nd Street
South, Arlington, VA, 22202, United States of America,
1 - Identifying Shortfalls in Library Holdings through Analysis of
References in Faculty Publications
Ziyi Kang, University of Pittsburgh, 1048 Benedum Hall,
Department of Industrial Engineering, Pittsburgh, PA, 15261,
United States of America, , Shi Tang, Louis
Luangkesorn, Fan Zhang, Yunjie Zhang, Berenika Webster
University libraries measure their contribution to research in part through
providing reference material cited by faculty in their publications. One difficulty is
that article references are often abbreviated in non-standard ways. To compare
references with library holdings we apply text processing methods such as
normalization, string distances, and word splitting to determine if a reference is
held by the library. We apply this to one subject area and validate the accuracy of
the method.
2 - Assessing the Effects of Cross-Season Fairness Scheme on the
Competitive Balance of NFL Schedules
Niraj Pandey, University at Buffalo, 342 Bell Hall, North Campus,
Buffalo, NY, 14260, United States of America,
Murat Kurt, Mark Karwan,
Kyle Cunningham
The National Football League (NFL) is the highest revenue generating sports
league in the world. Although the league’s scheduling routine has evolved over
the years to ensure fairness, recent schedules exhibit significant imbalances in
several dimensions, particularly in teams’ rest durations between games. We
develop a two-phase MILP approach to create fairer schedules and evaluate the
price of the league’s practice of rotating venues of the games on a multi-year basis
on their competitiveness.
SA30
30-Room 407, Marriott
Research from 2015 Richard E. Rosenthal Early
Career Connection Program Participants
Sponsor: Analytics
Sponsored Session
Chair: Aurelie Thiele, Lehigh University, 200 W Packer Ave,
Bethlehem, PA, 18015, United States of America,
1 - Overview of “The Richard E. Rosenthal Early Career
Connection Program”
Aurelie Thiele, Lehigh University, 200 W Packer Ave, Bethlehem,
PA, 18015, United States of America,
This short talk will provide an overview of the Richard E. Rosenthal Early Career
Connecting Program, held in conjunction with the yearly Analytics conference in
the spring. It will focus on the 2015 edition of the program, co-organized by
Michelle Opp of SAS and myself.
2 - A Protein Scoring Function using Support Vector Machine
Shokoufeh Mirzaei, Cal Poly Pomona, 3801 West Temple Avenue,
Pomona, CA, 91768, United States of America, ,
Silvia Crivelli
In this paper a knowledge-based scoring function for quality assessment of
protein decoy models is developed. To this end, a benchmark data set from CASP
8, 9 and 10 is used. The dataset includes measurements of proteins structural
features that are seemingly having significant impacts on the quality of predicted
structures.
3 - Biologically-guided Radiotherapy Treatment Plan Optimization
Ehsan Salari, Wichita State University, 1845 Fairmount St,
Wichita, KS,
Radiotherapy treatments are delivered in daily fractions over the course of one to
several weeks. There is clinical evidence suggesting that patients with specific
tumor sites may benefit from delivering larger radiation doses in fewer fractions.
However, current treatment regimens use a fixed radiotherapy plan in all
fractions. This research aims at developing a spatiotemporal planning approach
that allows to investigate the potential benefit of temporal variation in the plan
across fractions.
SA31
31-Room 408, Marriott
Mathematical Optimization Models for Data Science
Sponsor: Data Mining
Sponsored Session
Chair: Dolores Romero Morales, Copenhagen Business School,
Porcelaenshaven 16 A, Frederiksberg, DK-2000, Denmark,
1 - Learning Tailored Risk Scores from Large Scale Datasets
Berk Ustun, PhD Candidate, MIT, 20 Highland Avenue Apt. 2,
Cambridge, MA, 02139, United States of America,
Cynthia Rudin
Risk scores are simple models that let user assess risk by adding, subtracting and
multiplying a few small numbers. These models are widely used in medicine and
crime prediction but difficult to learn from data because they need to be accurate,
sparse, and use integer coefficients. We formulate the risk score problem as a
MINLP, and present a cutting-plane algorithm to solve it for datasets with large
sample sizes. We use our approach to create tailored risk scores for recidivism
prediction.
2 - A Multi-objective Approach to Visualize Proportions and a Binary
Relation by Rectangular Maps
Dolores Romero Morales, Copenhagen Business School,
Porcelaenshaven 16 A, Frederiksberg, DK-2000, Denmark,
Emilio Carrizosa, Vanesa Guerrero
We address the problem of representing individuals, to which there are
proportions attached and a binary relationship, by means of a rectangular map,
i.e., a subdivision of a rectangle into rectangular portions, so that each portion is
associated with one individual, the areas of the portions reflect the proportions,
and portions adjacencies reflect adjacencies in the binary relationship. We
formulate this as a three-objective Mixed Integer Nonlinear Problem and
numerical results are presented.