Informs 2015

147 / 552

INFORMS Philadelphia – 2015
145
5 - Design of a Responsive Vaccine Supply Chain under Supply and
Demand Uncertainty
Stef Lemmens, KU Leuven, Naamsestraat 69 Box 3555, Leuven,
3000, Belgium, Nico Vandaele,
Catherine Decouttere
Both literature and industrial evidence emphasize the challenge and the
importance of the design of a responsive vaccine supply chain. We model the
interrelationships between multi-echelon inventory, production capacity and lead
time and take supply and demand uncertainty into account by the use of a
methodology which combines the guaranteed service approach and queueing
theory. Furthermore, we show the results of applying our methodology to a real-
life industrial rotavirus vaccine supply chain.
SD79
79-Room 302, CC
Software Demonstration
Cluster: Software Demonstrations
Invited Session
1 - Artelys - See the Artelys KNITRO 10.0 Optimization Solver
in Action
Richard Waltz, Senior Scientist, Artelys Corp
KNITRO is the premier solver for nonlinear optimization and recent winner of the
GECCO 2015 black-box optimization competition, finishing first among 28
solvers. This software demonstration will highlight the latest KNITRO features,
including a new object-oriented interface and new SQP algorithm for derivative-
free optimization (DFO). The demo will also provide an overview of how to
effectively use KNITRO in a variety of environments and applications, and present
recent benchmarking results for DFO and nonlinear optimization.
2 - GAMS Development Corp - GAMS – An Introduction
Steve Dirkse, Director of Optimization, GAMS Development Corp
This workshop will show you how to use the General Algebraic Modeling System
(GAMS) in an efficient and productive way. There will be an introduction to the
system and a presentation of the key concepts in GAMS. The largest part of the
workshop consists of hands-on exercises. Amongst others, it will be demonstrated
how GAMS interacts with other applications and you will see how to analyze and
debug problems using the tools available within GAMS.
Monday, 8:00am - 9:30am
MA01
01-Room 301, Marriott
Military O.R. and Applications III
Sponsor: Military Applications
Sponsored Session
Chair: Michael Hirsch, ISEA TEK, 620 N. Wymore Rd., Ste. 260,
Maitland, FL, 32751, United States of America,
1 - Electronic Attack Decision Framework using Pomdp
Brandon Ha, Sr. Systems Engr Ii, Raytheon Company,
2000 E. El Segundo Blvd, E1/B2208D, El Segundo, CA, 90245,
United States of America,
The objective of this research is to develop a suite of machine learning algorithms
to address the need for engaging with future advanced unknown agile RF threats
and co-evolve with the adversary’s response. Our approach uses POMDP to
represent the unobservable elements in the environment and actions that can
provide partial information about these elements – to learn (characterize) the
unknown emitters and then to predict the intent and deploy optimal EA
technique(s).
2 - Pursuit on a Graph using Partial Information: Max-delay
David Casbeer, Dr., Air Force Research Laboratory, 2210 8th
Street, B20146 R300, Wright Patterson AFB, OH, 45433, United
States of America, , Krishna Kalyanam,
Meir Pachter
The optimal control of a “blind” pursuer searching for an evader on a graph is
presented. At specific locations on the graph (road network), unattended ground
sensors (UGS) have been placed which detect the intruder. The pursuer (UAV)
visits the sensors and decides where to travel in order to capture the evader. An
algorithm is presented to compute the maximum initial delay for which capture is
guaranteed. The algorithm also returns the corresponding optimal pursuit policy.
3 - Improved Sensor Placement in Multistatic Sonar Networks
W. Matthew Carlyle, Naval Postgraduate School,
Emily Craparo, Mumtaz Karatas,
Christoph Hof
Multistatic sonar networks containing non-collocated sources and receivers
represent an important generalization of traditional sonar systems. Although they
convey many tactical and operational advantages, multistatic sensor networks are
difficult to model and to employ optimally. We discuss the multistatic sensing
problem and describe algorithms for placing sources and receivers.
4 - Optimal Deployment of Network Defenses
David Myers, Research Engineer, United States Air Force, 26
Bedford Drive, Whitesboro, NY, 13492, United States of America,
Optimally deploying an ever-growing slate of network defense capabilities, while
maintaining the ability to perform the mission, is a critical component of future
USAF operations. Utilizing a system’s attack graph, this defense configuration
problem (DCP) is a network interdiction problem where the network defender is
the interdictor and the attacker is the evader. The purpose of this presentation is
to formulate and describe the DCP and discuss extensions into a dynamic posture
problem.
MA02
02-Room 302, Marriott
Game Theory in Practice for Homeland Security
Cluster: Homeland Security
Invited Session
Chair: Milind Tambe, USC, 941 Bloom Walk, Los Angeles, CA,
United States of America,
1 - Game Theoretic Applications in Coast Guard Operations
Erich Stein, USCG, 1 Chelsea St., New London, CT, 06339,
United States of America, Craig Baldwin,
Sam Cheung
The Coast Guard has tested and operationalized game theory applications in
several mission areas including port security and fisheries. A model was created to
mitigate effects of illegal fishing and generate schedules for USCG assets. The Port
Resilience Operational Tactical Enforcement to Counter Terrorism (PROTECT)
game model optimizes limited security resource allocations. Finally, development
of innovative patrol strategies for drug and migrant interdiction efforts is ongoing.
MA02