2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
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103C-MCC
Advances in Energy Systems Modeling
Sponsored: Energy, Natural Res & the Environment, Energy II Other
Sponsored Session
Chair: Rudolf Gerardus Egging, Norwegian University of Science &
Technology, Trondheim, Trondheim, 00000, Norway,
1 - Plug And Abandonment Of Offshore Oil And Gas Fields.
Steffen J. Bakker, Norwegian University of Science and
Technology,
At the end of a wells life-cycle, the well has to be permanently abandoned. This
process is called plug and abandonment (P&A). Decisions in the P&A process
depend heavily on uncertain factors such as oil and gas prices, rig rates or well
states. Moreover, these decisions have to be taken at different levels. In this
presentation we discuss a classification of the P&A process into an operational,
tactical and strategic level. For each of these levels we present a corresponding
model, where we make use of real options theory and the frameworks of integer
and stochastic programming.
2 - Trading Off Demand Side Flexibility Vs. Supply Side Flexibility And
Storage In The Electricity System
Hector Maranon-Ledesma, Norwegian University of Science and
Technology,
Demand Side Management (DSM) permits a reduction in peak load consumption,
a more adaptable demand of electricity, allowing shuting down high emission
power plants, and the intermittent renewable resources to be better exploited by
the use of flexibility mechanisms.
The EMPIRE electricity sector model is a long-term investment stochastic model.
This model has been improved by including DSM at the operational level. The
contributions of this work are including DSM in a large scale electric system and
highlighting the importance that DSM might acquire in the future European
power system.
3 - The Effect Of Drivers Elasticity On The Optimal Pricing And
Management Of Electric Vehicles Charging
Chiara Bordin, Norwegian University of Science and Technology,
Trondheim, Norway, , Stig Ødegaard
Ottesen, Asgeir Tomasgard, Siri Bruskeland Ager-Hanssen,
Siri Olimb Myhre
The increasing demand for Electric Vehicles (EV) charging puts pressure on the
power grids as in some situations the power consumption can exceed the grid
capacity. We propose a mathematical model for the indirect control of EV
charging that finds an optimal set of price signals to be sent to the drivers
according to their flexibility. The objective is to satisfy the demand when there is a
capacity lack by minimizing the curtailment of loads and prioritizing the loads
shifting. The key contribution is the use of the elasticity concept to forecast the
drivers reactions to the price signals. Sensitivity analyses are presented to
investigate the elasticity effect on prices and loads management.
4 - Risk Aversion In Imperfect Natural Gas Markets.
Rudolf Gerardus Egging, Norwegian University of Science &
Technology,
We consider risk aversion by natural gas supply companies considering
investment in conventional and shale gas resources in a stochastic multi-period
mixed complementarity problem. Uncertainty considered includes political risk
and resource sizes. We consider shale gas investment in Poland and Ukraine in a
realistic market setting in Europe. We discuss investment decisions and profits for
varying levels of risk aversion.
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104A-MCC
Dense Clusters in Network Optimization
Sponsored: Optimization, Network Optimization
Sponsored Session
Chair: Vladimir Stozhkov, University of Florida, 2330 SW Williston Rd,
Apt 2826, Gainesville, FL, 32608, United States,
1 - Relative Clique Relaxations In Complex Networks
Vladimir Boginski, University of Central Florida,
Real-world complex networks exhibit clustered structure: certain groups of nodes
(vertices) form “cohesive” or “highly connected” clusters (can also be referred to
as “communities”), which can be rigorously characterized using graph-theoretic
concepts. In this presentation, we will focus on so-called relative clique relaxation
models, which are obtained by relaxing certain metrics that attain their maximum
possible values on a clique: edge density, minimum vertex degree, and vertex
connectivity. We will discuss optimization problems of identifying such clusters in
networks, as well as related asymptotic results on phase transitions in random
graphs.
2 - Robust Network Clusters With Small-world Property
Jongeun Kim, University of Florida, Gainesville, FL,
United States, , Alexander Veremyev,
Vladimir Boginski, Oleg A Prokopyev
Networks are popular and effective tools for analyzing real-world systems, such as
telecommunication, transportation, and social networks. Network robustness is
one of the important issues, because some undesired failures may affect
connectivity and functionality of a network. The ideal robust cluster in a network
is a clique and clique-relaxation research have been developed in recent decades.
In this talk we will address small-world clusters that are robust but also have
certain natural properties.
3 - Detecting Essential Proteins Using A Novel Star Centrality Metric
Mustafa Can Camur, North Dakota State University, Fargo, ND,
United States,
In this talk, we propose a new centrality metric (referred to as star centrality),
which aims to incorporate information from the closed neighborhood of the node,
rather than strictly from the node itself. More specifically, we turn our focus to
degree centrality and show that in the complex protein-protein interaction
networks it is a naive metric that can lead to misclassifying importance in the
network. We portray the success of the new metric using protein-protein
interaction networks, and investigating the significant difference in the
importance of individual nodes we observe when transitioning from node degree
centrality to star degree centrality.
4 - Estimating The Maximum IUC Using SDP Relaxations
Eugene Lykhovyd, Texas A&M University, ,
Sergiy Butenko
If you have a simple, undirected graph, the Independent Union of Cliques (IUC)
problem is to find the maximum subset of vertices, in which every connected
component is a clique. It is known that this problem can be formulated on 3-
uniform hypergraphs as the maximum weak independent set. We propose the
estimates for IUC problem based on different SDP relaxations, extending the
Lov\’asz estimate for the maximum stable set. The comparison of different
approaches is also presented.
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104B-MCC
Convex Relaxations for Nonconvex
Polynomial Optimization
Sponsored: Optimization, Integer and Discrete Optimization
Sponsored Session
Chair: Daniel Bienstock, Columbia University, 116th and Broadway,
New York, NY, 10027, United States,
1 - LP And SOCP-based Algebraic Relaxations For
Polynomial Optimization
Amir Ali Ahmadi, Princeton University,
We present ongoing work on solving polynomial optimization problems using
linear and convex relaxations based on a number of ideas, including separation
from the set of rank-1 psd matrices, and, in particular, the method of approximate
representation of continuous variables as weighted sums of binary variables. We
will discuss theory and computational practice. Joint work (Gonzalo Munoz,
Chen Chen and Daniel Bienstock).
2 - Online First-order Framework For Robust Convex Optimization
Fatma Kilinc-Karzan, Carnegie Mellon University,
, Nam Ho-Nguyen
We present a flexible iterative framework to approximately solve robust convex
optimization problems. Our results are based on weighted regret online convex
optimization and online saddle point problems. A key distinguishing feature of
our approach from prior literature is that it requires access to only cheap first-
order oracles for each constraint individually and does simple online updates in
each iteration while maintaining the same convergence rate. For strongly convex
functions, we also establish a new improved iteration complexity. As a result, our
approach becomes much more scalable and hence preferable in large-scale
applications from machine learning and statistics domains.
3 - New And Old Results On Polynomial Optimization
Daniel Bienstock, Columbia University,
We present ongoing work on solving polynomial optimization problems using
linear and convex relaxations based on a number of ideas, including separation
from the set of rank-1 psd matrices, and, in particular, the method of approximate
representation of continuous variables as weighted sums of binary variables. We
will discuss theory and computational practice, and attempt to relate our work to
earlier results by Renegar and Barvinok. Joint work (Gonzalo Munoz, Chen Chen
and Daniel Bienstock).
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