Informs 2015

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INFORMS Philadelphia – 2015
263
TA16
16-Franklin 6, Marriott
Disjunctive Conic and Optimization Problems
Sponsor: Optimization/Linear and Conic Optimization
Sponsored Session
Chair: Julio Goez, Postdoctoral Fellow, Ecole Polytechnique Montreal
and GERAD, 2900 Boulevard Edouard-Montpetit, Montréal, QC, H3T
1J4, Canada,
1 - A Generalized Trust Region Subproblem with Hollows and
Non-Intersecting Linear Constraints
Boshi Yang, The University of Iowa, 14 MacLean Hall, Iowa City,
IA, 52242, United States of America,
Samuel Burer, Kurt Anstreicher
We study an extended trust region subproblem (eTRS) in which a nonconvex
quadratic function is minimized over a structured nonconvex feasible region: the
unit ball with r hollows (or holes) and m linear cuts. Under some non-
intersecting assumptions, when r = 0 or when r = 1 and m = 0, it is known that
the eTRS has a tight, polynomial-time solvable conic relaxation. We show that the
conic relaxation is also tight for general r and m precisely when some non-
intersecting assumptions are satisfied.
2 - On Disjunctive Conic Cuts: When They Exist, When They Cut?
Mohammad Shahabsafa, Lehigh University, 14 Duh Dr, Apt. 221,
Bethlehem, PA, 18015, United States of America,
The development of Disjunctive Conic Cuts (DCCs) for MISOCO problems has
recently gained significant interest in the optimization community. Identification
of cases when DCCs are not existing, or not useful, saves computational time. In
this study, we explore cases where either the DCC methodology does not derive a
DCC which is cutting off the feasible region, or a DCC does not exist. Among
others, we show that deriving DCCs directly for p-order cone optimization
problems seems to be impossible.
3 - Disjunctive Conic and Cylindrical Cut Management Strategies for
Portfolio Optimization Problems
Sertalp Cay, Lehigh University, 200 W Packer Ave, Bethlehem,
PA, 18015, United States of America, ,
Tamás Terlaky, Julio Goez
Disjunctive conic and cylindrical cuts lead significant positive impact while solving
Mixed Integer Second Order Cone Optimization (MISOCO) problems. The
decision for adding and removing these cuts should take depth of the cut and
structure of the problem into consideration. In this study, we explore strategies to
apply these novel cuts to discrete portfolio optimization problems within a
Branch-and-Conic-Cut software package. Preliminary results are provided to
compare these strategies.
4 - Novel Family of Cuts for SDP Relaxations for Some Classes of
Combinatorial Problems
Elspeth Adams, Miguel Anjos
k-projection polytope constraints (kPPCs) are a family of constraints that tighten
SDP relaxations using the inner description of small polytopes, as opposed to the
typical facet description. We examine the properties of kPPCs, methods for
separating violated kPPCs and their impact on the bounds in a cutting plane
framework. Problems satisfying the required projection property, such as the
max-cut and stable set problems, will be considered and results will focus on large
instances.
TA17
17-Franklin 7, Marriott
Network Resilience and Applications
Sponsor: Optimization/Network Optimization
Sponsored Session
Chair: Konstantin Pavlikov, University of Florida, 1350 N. Poquito
Road, Shalimar, FL, 32579, United States of America,
1 - Resilient and Structurally Controllable Supply Networks
under Disruptions
Amirhossein Khosrojerdi, The University of Oklahoma, 202 West
Boyd Street, Suite 218, Norman, Ok, 73071, United States of
America, Farrokh Mistree, Janet K. Allen,
Krishnaiyan Thulsiraman
A resilient supply network is one that has the ability to recover quickly from
disruptions and ensure customers are minimally affected. Designing the structure
of supply networks to be controllable is a way toward resilience. A three-stage
method is proposed to design a resilient and controllable supply network under
structural disruptions. The method is exercised using an example from the
petroleum industry.
2 - Embedding Resilience on Logistic and Supply Chain Networks
Jose Santivanez, Associate Professor, Universidad del Turabo, P.O.
Box 3030, Gurabo, PR, 00778, Puerto Rico,
Emanuel Melachrinoudis
This paper develops models for improving resilience to disruptions on critical
infrastructures such as logistics and supply chain networks through locational,
coverage, and path selection decisions. Network resilience is measured by the
ratio of the delivered amount of service over the total requested service when a
propagating disruption occurs. Availability of service depends on the capability of
the network to establish connectivity between service facilities and customers.
3 - Improving Supply Chain Network Resiliency with Preferential
Growth Decision Making
Ashley Skeete, PhD Fellow, Western New England University,
1215 Wilbraham Road, Springfield, MA, 01119, United States of
America, , Julie Drzymalski
Network resiliency is the ability to maintain operations and connectedness under
the loss of some structures or functions. This research develops decision making
techniques in the supply chain context to improve resiliency of existing supply
chain networks as they grow with time. Consideration is given to factors such as
network topology, production requirements, the presence of redundancies and
cost.
4 - Hub Location-allocation for Combined Fixed-wireless and
Wireline Broadband Access
Ramesh Bollapragada, Professor, College of Business, San
Francisco State University, 1600 Holloway Avenue, San Francisco,
CA, 94132, United States of America, ,
Uday Rao, Min Li, Junying Wu
This paper studies a telecommunications hub location model that includes the
classical capacitated facility location problem on a wireline network, as well as a
wireless network with technological as well as capacity constraints. There are
multiple wireline and wireless hub types, differing in costs and capacities. We
present a mathematical model to maximize network profit, build and test a quick
greedy heuristic with the optimal, and conduct sensitivity analysis using
representative data.
TA18
18-Franklin 8, Marriott
Scientometric Data Analytics
Cluster: Modeling and Methodologies in Big Data
Invited Session
Chair: Dohyun Kim, Myongji University, Yongin, Korea,
Republic of,
1 - Ranking Outliers in Patent Citation Network using Attributes and
Graph Structure
Ali Tosyali, Rutgers, the State University of New Jersey, Dept. of
ISE 96 Frelinghuysen Road, CoRE Building, Room 201,
Piscataway, NJ, United States of America,
, Byunghoon Kim, Jeongsub Choi,
Byoung-yul Coh, Jae-min Lee, Myong K (MK) Jeong,
Andrew Rodriguez
Being able to rank patents in outlierness is a crucial task for patent analysis. In the
past, existing general outlier ranking methods have been applied to patent data.
In this work, we propose a new outlier ranking method developed especially for
patents in attributed patent citation network. We utilized both graph structure
and attributes to rank outlier patents in patent citation network.
2 - Scientometric Analysis of Carbon Capture and Storage Research
Faezeh Karimi, Dr, University of Sydney, Project Management,
Sydney, 2006, Australia,
Rajab Khalilpour
This study investigates the evolutionary trends of the international collaborations
among the research community of carbon capture and storage (CCS) by looking
at the collaboration network of countries publishing on CCS. The study elaborates
how both international collaboration network and knowledge structure of the
field have notably developed and interlinked over the years especially after 2005
during which almost 94% of the publications appeared.
3 - Keyword Hierarchy Detection using Keyword Network Analysis
Dohyun Kim, Myongji University, Yongin, Korea, Republic of,
We Shim, Oh-jin Kwon,
June Young Lee, Sejung Ahn
We developed a keyword hierarchy detection algorithm using the keywork
network. Using the detection method, the hierarchy of keywords collected from
the same semantic field may be built.The keyword hierarchy detection method
can be used for a automatic preprocessing step to refine keywords in various topic
modeling methods.
TA18