Informs 2015

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INFORMS Philadelphia – 2015
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MB24
24-Room 401, Marriott
Data Mining and Network Inference for Social and
Health Application II
Sponsor: Artificial Intelligence
Sponsored Session
Chair: Sung Won Han, New York University, 650 First Avenue, New
York, NY, United States of America,
Co-Chair: Chen Kan, University of South Florida, 4202 E. Fowler Ave.
ENB118, Tampa, FL. United States of America,
1 - Optimizing Display Advertising in Online Social Networks
Zeinab Abbassi, PhD Candidate, Columbia University,
1214 Amsterdam Ave, 450 CSB, New York, NY, 10027,
United States of America,
Conventional online advertising methods need to be customized for OSNs. We
propose probabilistic models and study the problem: given a number of
impressions, what is the optimal order of users to show the ad to, to maximize the
expected number of clicks? We show that this problem is hard to approximate.
Therefore, we propose several heuristic algorithms. We evaluate the performance
of these heuristics on real data sets, and observe that our two-stage heuristic
outperforms baselines.
2 - Blood Donation Tailoring Problem to Improve Blood
Supply Management
Guven Kaya, PhD Student, Industrial Engineering, University of
Houston, E206 Engineering Bldg 2, Houston, TX, 77204,
United States of America, , Ali Ekici
Blood donation tailoring is to identify blood donation types and collect blood
products. Donors perform donation types that provide blood products to patients,
having collection/inventory/spoilage costs. We collect data about donation types
with demand, cost, time, eligibility percentages, compatibility from blood banks.
We develop MIP models to find collected/spoiled/carried blood product amount
on single and multi-period settings. We provide results based on data from blood
donation centers.
MB26
26-Room 403, Marriott
Data Analytics Applications for Smart Industries
Cluster: Globalization and International Activities
Invited Session
Chair: Grace Lin, Data Analytic Technology and Applications (DATA),
Data Analytic Technology and Applications (DATA), Taipei,
Taiwan - ROC,
1 - Is the Conventional Association Analysis Practical for Big Data
Analytics? New Perspectives on Application and Computation
Hao-Ting Pai, Data Analytics Technologies & Applications
Research Institute, Institute for Information Industry,
Taiwan - ROC,
Association analysis has been proven an NP-Complete problem. Owing to the
inevitable challenge, it is necessary to devise an alternative way of discovering
representative patterns. We present relative patterns discovery (named RPD) for
big data analytics, which possesses four features: effectiveness, efficiency,
panorama, and scalability.
2 - Towards Industry 4.0: Applying Big Data Analytics to Improve
Manufacturing Performance
Fish Yu, Data Analytics Technologies & Applications Research
Institute, Institute for Information Industry, Taiwan - ROC,
As a step towards the development of cyber-physical systems which play an
important role in the transformation of manufacturing industry to the next
generation known as Industry 4.0, this talk describes a log analytics framework
that is capable of collecting, managing and analyzing large amount of machine
data to enable real-time and predictive decision-making across various
manufacturing processes. Experimental results using realistic data from
semiconductor packaging tools show the effectiveness of the proposed
framework.
3 - Green Multi-temperature Logistics using Time-dependent
Data Analysis
Wei-Ting Chen, Data Analytics Technologies & Applications
Research Institute, Institute for Information Industry, Taiwan -
ROC,
Multi-temperature food logistics contributes a considerable amount of greenhouse
gas due to fuel burn and HFCs and PFCs generated by refrigeration. In this talk,
we will introduce how to estimate emissions depend on various levels of traffic
condition, temporal demand patterns, delivery time windows, and different
temperature control techniques. It helps carriers to respond to green policies of
governments.
4 - Emerging Trends in ICT: using Big Data Analytics to Infuse New
Energy into Smart Tourism Industry
Tim Lin, Data Analytics Technologies & Applications Research
Institute, Institute for Information Industry, Taiwan - ROC,
As many leading global organizations have applied Big Data Analytics to various
public and commercial areas, valuable applications such as consumer insight,
business operations optimization, and service innovation have been continuously
increasing. In this talk, we will introduce a smart tourism solution which provides
tourists real-time, personal, and proactive services by leveraging Big Data
Analytics, resulting in a deep and authentic experience. The developed solution
can support tourism-related businesses to connect with prospective customers and
build responsive, efficient, and health smart cities and homelands.
MB27
27-Room 404, Marriott
Advances in Multiobjective Programming
Sponsor: Multiple Criteria Decision Making
Sponsored Session
Chair: Margaret Wiecek, Department of Mathematical Sciences,
Clemson University, Clemson, SC, 29634, United States of America,
1 - Parametric Simplex Algorithm for Linear Vector
Optimization Problems
Firdevs Ulus, Princeton University, ORFE, Sherrerd Hall,
Princeton, NJ, 08544, United States of America,
Birgit Rudloff, Robert Vanderbei
A parametric simplex algorithm for linear vector optimization problems is
proposed. The efficiency of the algorithm is compared with Benson’s algorithm
and the multiobjective simplex algorithm. For nondegenerate problems it
outperforms Benson’s algorithm and is on par with the multiobjective simplex
algorithm. For degenerate problems Benson’s algorithm excels the simplex-type
algorithms; however, the proposed algorithm performs much better than the
multiobjective simplex algorithm.
2 - An LP-based Branch-and-bound Algorithm for Biobjective Mixed
Integer Programs
Nathan Adelgren, Clemson University, Department of
Mathematical Sciences, Clemson, SC, 29634, United States of
America, , Akshay Gupte
We introduce a new LP-based branch-and-bound (BB) method for solving
biobjective mixed integer linear programs (BOMILP). New branching, fathoming,
cutting plane and node relaxation techniques are incorporated into a traditional
BB framework. Computational results show that this method is competitive with
current techniques for BOMILP.
3 - The Quadrant Shrinking Method for Solving Triobjective
Integer Programs
Martin Savelsbergh, Prof, H. Milton Stewart School of Industrial
& Systems Engineering, Georgia Institute of Technology, 765 Ferst
Dr NW, Atlanta, GA, 30332-0205, United States of America,
Hadi Charkhgard,
Natashia Boland
We present a new variant of the full (p-1)-split algorithm for finding all
nondominated points of a triobjective integer program. The algorithm is easy to
implement and solves at most 3n+1 integer programs, where n is the number of
nondominated points. Computational experiments demonstrate its efficacy.
4 - Optimizing a Linear Function Over the Efficient Set of a
Multi-objective Integer Program
Hadi Charkhgard, University of Newcastle, University Drive,
Callaghan, Australia, ,
Natashia Boland, Martin Savelsbergh
We present a new algorithm to optimize a linear function over the set of efficient
solutions of a multi-objective integer program. Because the algorithm maintains
both a lower and an upper bound on the optimal objective value, it can easily be
converted into a fast approximation algorithm. Finally, we demonstrate that the
algorithm can be used to efficiently compute the nadir point of a multi-objective
integer program.
MB24