Informs 2015

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INFORMS Philadelphia – 2015
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4 - P-center and P-dispersion Problems: A Bi-criteria Analysis
Golbarg Kazemi Tutunchi, North Carolina State University,
1916 Trexler Ct, Raleigh, NC, 27606, United States of America,
, Yahya Fathi
We consider the p-center and the p-dispersion problems in the context of a bi-
criteria location analysis. We discuss a mathematical programming approach to
obtain a non-dominated point with respect to these two objectives, and an exact
method to obtain the corresponding non-dominated frontier. Through a
computational experiment we demonstrate the effectiveness of this approach for
different instances of the problem.
5 - A Cut and Branch Approach for a Class of Bi-Objective
Combinatorial Optimization Problems
Sune Lauth Gadegaard, PhD fellow, Department of Economics
and Business, Aarhus University, Fuglesangs Allé 4, Bygning
2622, lokale 315a, Aarhus V, 8210, Denmark,
, Matthias Ehrgott
In this talk we discuss a cut and branch approach for bi-objective optimization
problems with integer outcome vectors. The approach improves the LP-relaxation
by adding cuts at each extreme point of the efficient frontier of the LP-relaxation.
After improving the LP-relaxation, we propose a branch and bound algorithm
which alternately branches in objective space and in decision space. Experimental
results for the single source capacitated facility location problem is reported.
WC28
28-Room 405, Marriott
Optimization Stochastic V
Contributed Session
Chair: Yasaman Kazemi, North Dakota State Univesrity, NDSU Dept.
2880, P.O. Box 6050, Fargo, ND, 58108, United States of America,
1 - Multistage Stochastic Programming under Endogenous and
Exogenous Uncertainties
Robert M. Apap, Carnegie Mellon University, 5000 Forbes
Avenue, Pittsburgh, PA, 15213, United States of America,
, Ignacio E. Grossmann
We address the modeling and solution of mixed-integer linear multistage
stochastic programming problems involving endogenous and exogenous
uncertain parameters. We propose a composite scenario tree that contains both
types of parameters. We then present new theoretical model-reduction properties
to drastically reduce the number of non-anticipativity constraints. Lagrangean
decomposition and a sequential scenario decomposition heuristic are used to
solve large-scale instances.
2 - Stochastic Optimization of Downstream Petroleum Supply Chain
under Uncertainties
Yasaman Kazemi, North Dakota State Univesrity, NDSU Dept.
2880, P.O. Box 6050, Fargo, ND, 58108, United States of America,
, Joseph Szmerekovsky
An integrated multi-product multi-echelon and multi-mode supply chain design
is studied in the downstream petroleum supply chain under the risk of facility
disruptions. Two-stage stochastic model is proposed to minimize the expected
total costs by optimizing the strategic and tactical decisions and selecting
appropriate mitigation strategies. In addition, Geographic Information System
(GIS) is used to locate facilities, obtain realistic transportation data, and to
visualize the process.
3 - Risk-averse Wind Power Investment through Unified Stochastic
and Robust Optimization
Kun Zhao, Department of Industrial and Systems Engineering
The University of Florida, FL, United States of America,
, Yongpei Guan
A unified stochastic and robust optimization approach is proposed for the wind
power investment problems. Two models are developed: a short-term risk-averse
wind power investment problem for market participants, and a long-term
simultaneous wind power and transmission investment problem for vertically
integrated utilities. By reformulation, tractable formulations can be obtained and
solved in finite time. Computational results are shown for the effectiveness of our
proposed model and solution approaches.
WC29
29-Room 406, Marriott
Decision Analytics Applications in the Media Industry
Sponsor: Analytics
Sponsored Session
Chair: J. Antonio Carbajal, Sr Operations Research Analyst,
Turner Broadcasting System, Inc., 1050 Techwood Dr., Atlanta, GA,
United States of America,
1 - Commercial Time Management Applications in the Media Industry
J. Antonio Carbajal, Sr Operations Research Analyst, Turner
Broadcasting System, Inc., 1050 Techwood Dr., Atlanta, GA,
United States of America, ,
W. Chaar
Advertisement-based networks face the challenge of optimally allocating their
commercial time capacity to meet audience levels guaranteed to their advertisers.
This presentation introduces two systems that support this objective: 1) A spot
scheduling engine that maximizes deal delivery while honoring several placement
constraints and 2) A make-goods allocation engine that maximizes the liability
inventory value and meets advertiser requirements of selling title mix and weekly
unit distribution.
2 - Competitive Audience Estimation
W. Chaar, Analytics, Data & Decision Sciences, VP, 106 N Denton
Rd, 210, Dallas, TX, 75019, United States of America,
J. Antonio Carbajal, Peter Williams
A consumer choice modeling approach is developed and used to model audience
behavior across competing media contents. The methodology demonstrates the
capability of the approach to generate accurate predictive results of audiences.
3 - Television Programming Optimization in the 24-hour Cable
Network Environment
Peter Williams, Sr. Operations Research Analyst, Turner
Broadcasting System, Inc., 1050 Techwood Dr., Atlanta, GA,
30308, United States of America, ,
W. Chaar, J. Antonio Carbajal
A cable network programmer’s main objective is to create program schedules that
attract viewers. The mix of available programs and various scheduling constraints
introduce complexity to organizing a 24-hour program schedule. With Nielsen
data, the authors develop a model to predict ratings using features of a program
schedule. Using this model, TV program scheduling is formulated as an
optimization problem with the objective of maximizing ratings given program
airtime constraints.
WC30
30-Room 407, Marriott
Information Systems II
Contributed Session
Chair: Harris Kyriakou, Stevens Institute of Technology, 1 Castle Point
on Hudson, School of Business 642, Hoboken, NJ, 07030,
United States of America,
1 - Cooperate to Dominate?: Empirical Analysis of Cooperation
Decisions on Technological Innovation
Ashish Kumar Jha, Doctoral Student, Indian Institute of
Management Calcutta, Diamond Harbor Road, Joka, Kolkata,
WB, 700104, India, , Indranil Bose
We analyze the importance of cooperation factors and cooperation partners for
product and process innovation for Chinese firms. We also test the relationship
between product and process innovation which leads to confirmation of our
hypothesis that continuous process innovation has a rub off effect on product
innovation and product innovation increases but vice versa is not true. We arrive
at the conclusions based on analysis of innovation data of over 900 Chinese firms.
2 - Commercial Companies’ Open Source Strategies – When Should
Competitive Companies Support the Same Operation
Ying Liu, Xi’an Jiaotong University, No.28 Xianning Road,
Beilin District, Xi’an, China,
Nowadays many firms have been involved with open source software through
various ways, such as contributing code and providing support to open source
community. They do this for profit, mostly through complementary product or
service. How much effort should they put into open source project and does their
competitor’s contribution affect their behavior? How would they design additive
product? Does free-riding problem really hurt and which kind of license can
mitigate it?
WC30