
Fields Industrial Optimization Seminar
200708

Supported by



The inaugural meeting of the Fields Industrial Optimization Seminar
took place on November 2, 2004. This series will meet once a month,
on the first Tuesday, in the early evening. Each meeting will comprise
two related lectures on a topic in optimization; typically, one
speaker will be a universitybased research and the other from the
private or government sector.We welcome the participation of everyone
in the academic or industrial community with an interest in optimization
 theory or practice, expert or student.
Please subscribe to the Fields mail list
to be informed of upcoming seminars.
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SEMINARS
Seminars start at 5:00 pm at the Fields Institute, 222 College
Street, Room 230
Tuesday, June 3, 2008 
Amy Cohn, University of Michigan
"Optimized" Airline Plans and Operational Realities
This talk will investigate the role of Operations Research
in airline planning and, in particular, investigate the link
between an airline plan and its operational robustness. I
will provide a brief review of the airline schedule planning
process, discuss the relationship between a planned airline
schedule and its operational performance, highlight sources
of delay propagation, and describe methods for improving robustness
in the planning process and for recovering from disruptions
during dayofoperations.
and
Timothy Jacobs, American Airlines (PastPresident
of AGIFORS, the Airline Group of IFORS)
Integrating O&D Passenger Effects into the Airline
Scheduling Process
This paper presents an overview of the fleet assignment,
schedule development and revenue management processes airlines
typically use to develop, fleet and manage the seat inventory
of their schedule. In addition, this paper presents a methodology
for incorporating O&D network and pricing effects into
the fleet assignment process. To illustrate the O&D fleeting
concept and its benefits, we apply this concept to a typical
schedule planning scenario at American Airlines and a Demand
Driven Dispatch (D3) scenario where nearterm fleeting changes
improve the match between O&D passenger demand and available
aircraft capacity close to the day of departure for American
Eagle Airlines.

Tuesday, May 6, 2008 
C.T. Kelly, North Carolina State University
Optimal Design of Municipal Water Supply Portfolios with
Implicit Filtering
In this talk we describe an optimal design problem for a
portfolio of water rights, leases, and options in the Southwestern
Unites States. The design is based on a Monte Carlo model
of rainfall and demand. The design parameters encode the government's
response to demand and expected supply. The stochastic model
implies that the objective function, the cost of a city's
water supply for a year, is a discontinuous function of the
design parameters. Constraints on reliability and conditional
value at risk can only be tested when the simulation is complete
and are not given by explicit formulae. We show how the implicit
filtering method can solve the problem and exploit our knowledge
of the size of the noise.
and
Amr ElBakry, EXXON
Optimization in the Oil and Gas Industry: the Models and
the Challenges
Although optimization has been used extensively in refineries
since the 1950's, its use in other areas of the oil and gas
industry such as exploration, development, drilling, and production
has been relatively limited. Recent developments in optimization
technology and the increasing complexity in the abovementioned
activities led to a renewed interest in optimization as an
analysis and decisionsupport tool.
In this talk I will give an overview of the challenging optimization
problems facing the current and the future oil and gas exploration
and production activities. The resulting models cover almost
all areas of optimization technology, from continuous to combinatorial,
from linear to nonlinear and from deterministic to stochastic.
I will conclude the talk with few comments for those who are
aspiring to pursue careers as industrial mathematicians.

Tuesday, April 1, 2008 
Bartosz Protas, McMaster University
AdjointBased Optimization in Fluid Mechanics: Theory,
Computations and Industrial Applications
In this presentation we review solution methods for a class
of equality constrained optimization problems in fluid dynamics
governed by partial differential equations such as the NavierStokes
equation and other conservation equations. We show how such
PDEconstrained optimization problems can be efficiently solved
using a gradientbased approach. Since the control variable
in such problems is usually continuous, the main challenge
consists in determining the gradient of the cost functional
with respect to such infinitedimensional control, and we
demonstrate that this can be done conveniently by solving
a suitablydefined adjoint PDE system. We emphasize, in particular,
problems described by PDEs defined on variable domains, whose
treatment necessitates the use of specialized techniques,
such as the shapedifferential calculus. Application of the
presented approach to a number of classical problems in fluid
mechanics and thermodynamics will be discussed, including
optimal control for drag reduction, optimal state estimation
and optimization of interfacial phenomena (the Stefan problem).
We will conclude by presenting some industrial applications
concerning optimization of advanced welding techniques in
automotive industry.
and
Saroja Polavarapu, Environment Canada
Fourdimensional variational assimilation in the context
of weather prediction
Data assimilation involves combining observations with computer
model output to obtain a consistent, evolving 3dimensional
picture of the atmosphere. This process is used at operational
weather forecasting centres to produce initial conditions
for launching weather forecasts.
The mathematics of data assimilation is from estimation theory,
but in practice, there are many unique challenges and constraints
to contend with. Weather forecasting models simulate an ever
increasing number of nonlinear atmospheric processes, and
are very large with state space of dimension 10 to 100 million.
Such models require the fastest and largest supercomputers
in order to produce timely forecasts. At the same time, while
millions of observations are collected and distributed globally,
this is an order of magnitude smaller than the state vector.
Therefore, there are also too few observations to compute
the forecast error statistics needed for data assimilation.
Approximations are
thus necessary, and where possible, knowledge of atmospheric
dynamics provides guidance. This talk will provide an overview
of the
atmospheric data assimilation problem in the context of global
numerical weather prediction and will focus on the fourdimensional
variational assimilation technique which is operational at
Environment Canada.

Tuesday, March 11, 2008 
Jan Modersitzki, McMaster University
Numerical Methods for Image Registration
Image registration is one of the most challenging tasks within
digital imaging. Given two images R and T, one is looking
for a transformation y such that a deformed version T(y(x))
of T is similar to R. The problem arises, for example, when
images taken from different objects, perspectives, times,
or devices need to be compared or fused.
Image registration, and in particular medical image registration,
has been subject to extensive studies in the past years. Its
versatile and important applications have attracted researchers
from various branches. In this talk, we not only give an overview
on some new
and exiting approaches but also point out some of the computational
challenges associated with these approaches. Moreover, we
explain why variational based methods to image registration
naturally lead to large scaled and challenging optimization
problems. We
present various instructive examples and real life applications.
and
Vladimir Pekar, Philips Research North America
Image Registration in Radiation Therapy Planning
The changes in a patient’s anatomy during the course
of fractionated radiotherapy lead to uncertainties in radiation
delivery. This limits the treatment efficacy and can cause
severe side effects. The aim of adaptive imageguided radiation
therapy (IGRT) is to minimize these uncertainties through
the use of additional imaging studies (including multimodal
imaging), which allows for highly individualized radiation
treatment plans. In doing so, deviations from the treatment
plan can be detected at an early stage to correctively adjust
the plan parameters. Image registration is the key technological
component for successful implementation of IGRT.
In this talk, we will review and discuss several classes of
image registration methods and their applications in radiation
therapy planning. A comparative presentation of voxelbased,
modelbased, and featurebased registration methods will be
given. Illustrative examples using real clinical data will
also be presented.

Tuesday, February 5, 2008 
John W. Chinneck, Carleton University
The Maximum Feasible Subsystem Problem and Applications
Given an infeasible set of linear constraints, the Maximum
Feasible Subsystem Problem (MaxFS) consists of finding the
largest cardinality feasible subset of the constraints. A
wide variety of algorithms for the solution of this problem
have been proposed in recent years. These solution algorithms
will be summarized, and applications in areas as diverse as
machine learning, statistics, computational biology, digital
video broadcasting, etc. will be described.
and
Mauricio G. C. Resende, Lead Member of Technical Staff,
Algorithms & Optimization Research Department
AT&T Labs Research
Some combinatorial optimization problems arising in telecommunications
Combinatorial optimization problems are abundant in the telecommunications
industry and the successful solution of these problems has
played an important role in telecommunications and its widespread
use. Optimization arises in problems as varied as planning
and design of optical and wireless networks, routing, restoration,
network survivability, ecommerce, and search engine design.
In this talk, we report on five problems that we have recently
come across while working at an industrial research center
of a large communications services company. The focus of our
research is on developing heuristics to find goodquality
solutions for these problems.
Telephone migration occurs when an organization upgrades
to a newer phone switch (PBX) and needs to move all the phones
using the old switch to the new one. PBX switches implement
many features in which groups of phones can interact. One
example is the "multiline hunt group" where up
to 100 phones are placed in a cycle and any call coming into
any phone in the group will cycle through the group until
it is answered. Another example is "call pickup"
where any phone in the group can answer any call made to other
phones in the group. Given a number of periods in which to
migrate the phones and a maximum number of phones that can
be moved per period, we want to complete the migration process
in the time horizon while minimizing the disruption to the
features provided by the switches.
Traffic migration occurs when traffic is to be moved from
an outdated network to a new one. At each time period, a node
in the old network is decommissioned and deloaded. i.e. all
traffic coming into it or going out of it is moved to a given
node in the new network. After a few nodes have been decommissioned,
there will be some traffic in the old network, some traffic
in the new network, and some traffic between the two networks
for which temporary capacity will have to be provided. The
objective is to minimize this capacity by determining the
order in which the old nodes are decommissioned.
The Internet is divided into many routing domains, called
autonomous systems. An autonomous system, or simply AS, is
a network that consists of routers and links connecting the
routers. These ASes interact to control and deliver Internet
Protocol (IP) traffic. They typically fall under the administration
of a single institution, such as a company, a university,
or a service provider. Intradomain traffic engineering aims
to make more efficient use of network resources within an
AS. Interior Gateway Protocols such as OSPF (Open Shortest
Path First) are commonly used to select the paths along which
traffic is routed within an AS. These routing protocols direct
traffic based on link weights assigned by the network operator.
Each router in the AS computes shortest paths and creates
destination tables used to direct each packet to the next
router on the path to its final destination. Given a set of
traffic demands between origindestination pairs, the "OSPF
weight setting problem" consists in determining weights
to be assigned to the links so as to optimize a cost function,
typically associated with a network congestion measure.
It is also the role of the routing protocol to specify how
the network should react to changes in the network topology,
such as arc or router failures. In such situations, IP traffic
is rerouted through the shortest paths not of one or more
"pipes", where pipes can have different capacities
and costs. We consider a survivable IP network design problem,
where we need to assign OSPF weights and select a subset of
pipes to assign to each arc, aiming to produce efficient OSPFrouted
networks with minimum total "pipe" cost needed to
route
the required demand and handle any single arc or router failure.
In the optimal node placement problem for path disjoint network
monitoring we wish to carry out endtoend network performance
measurements between each of a given set of target nodes and
pairs of measurement nodes, under the constraint that the
pair of paths from each measurement node to the corresponding
target node are node disjoint. Arbitrary routes are disallowed
and we are constrained to obey standard network routing policies,
such as OSPF. The objective is to find the smallest cardinality
set of measurement nodes.

Tuesday, December 4, 2007 
Peter Sturdza, Desktop Aeronautics, Palo Alto, CA
Design Optimization of a Supersonic Natural Laminar Flow
Business Jet
Few aircraft are specifically designed to emphasize passive
laminar flow at the preliminary design stage. The Aerion natural
laminar flow supersonic business jet concept requires just
that. This paper discusses some details of the unique technology
developed for the design of Aerion’s revolutionary jet.
An overview of the laminar flow features of the configuration
are presented, along with a summary of the designoriented
transition prediction methodology used for aerodynamic design
of the airplane. Results from aerodynamic shape optimizations
of the business jet and of a new high Reynolds number supersonic
laminar flow experiment are also presented.
and
Sivakumaran Nadarajah, Department of Mechanical Engineering,
McGill University
Pushing the Limits of Optimum Shape Design for Unsteady
FlowsIn the past decade, aerodynamic shape optimization
has been the focus of attention due largely to advanced algorithms
that have allowed researchers to calculate gradients cheaply
and efficiently. The majority of work in aerodynamic shape
optimization has focused on the design of aerospace vehicles
in a steady flow environment. Investigators have applied these
advanced design algorithms, particularly the adjoint method,
to numerous problems, ranging from the design of twodimensional
airfoils to full aircraft configurations to decrease drag,
increase range, and reduce sonic boom. Researchers have tackled
these problems using many different numerical schemes on both
structured and unstructured grids.
Unlike fixed wing aircraft, helicopter rotors and turbomachinery
blades operate in an unsteady flow and are constantly subjected
to unsteady loads. The flight envelope of a helicopter rotor
is set by the compressibility effects experienced by the advancing
rotor blade and by the dynamic stall of the retreating blade.
As the helicopter forward flight speed increases, local supersonic
zones that terminate at a shock wave develop on the advancing
side, while at the retreating phase, the blade's velocity
relative to the air decreases and the blade approaches the
stall angle. This causes significant flow separation to occur
on the upper surface of the blade, which in turn produces
a loss in lift. All these issues have to be carefully taken
into consideration to fully appreciate the performance of
helicopter rotor blades.
Despite the recent efforts in ameliorating existing steady
flow aerodynamic shape optimization algorithms, there is a
considerable need to develop innovative and costeffective
optimal control techniques as well as new schemes for the
design of aerodynamic surfaces subjected to unsteady loads.
The goal is to push the limits on both the development of
new schemes for the solution of unsteady flows as well as
new algorithms for the design of aerodynamic shapes subject
to unsteady loads.

Tuesday, November 13, 2007 
Andras Prekopa, Rutcor, Rutgers Center for Operations
Research
Optimization Methods in Valuation of Financial Derivatives
and Financial Planning
Valuation of financial derivatives and financial planning
are two different directions in mathematical finance. Both
use optimization methods and we present a few recent models
and methodologies in both directions. Dynamic programming
problems are formulated for the valuation of the Bermudan
and American put and call, dividend paying options under the
BlackScholesMerton model for the asset price process. The
models are solved by formulas that are numerically evaluated.
Under more general conditions, the problem to approximate
the price of a derivative, by the use of lower and upper bounds,
is formulated as a special case of the classical moment problem.
The probability distribution of the asset price is unknown
but moment information is assumed to be available. Formulas,
as well as specially designed algorithms provide us with the
approximating values. Finally, we present recent results on
the use of VaR, CVaR and CVAR risk measures in optimal portfolio
composition problems.
and
Reha Tutuncu, Goldman Sachs
Optimization and Quantitative Portfolio Management
Optimization models and methods are central elements of quantitative
equity portfolio management platforms. They serve as sophisticated
tools for transfering the excess return ideas generated through
research and testing into portfolios that best represent these
ideas. In addition to the standard meanvariance optimization
models that are adjusted for trading costs, we will discuss
topics such as multiportfolio optimization (optimizing multiple
portfolios simultaneously while minimizing the joint market
impact costs) and multiperiod portfolio selection.

Tuesday, October 2, 2007 
Eva K. Lee, Director
Center for Operations Research in Medicine and HealthCare
School of Industrial and Systems Engineering, Georgia Institute
of Technology
and
Department of Radiation Oncology
School of Medicine
Emory University
Robust Optimization to Accommodate Effects of Systematic
Treatment Uncertainties
Efficient and reliable IMRT treatment planning is challenging
even when using only a single frozenintime CT scan of anatomic
structures. The challenge is intensified in 4D treatment
planning, which is based on highly expanded imaging datasets
that provide views of structure shape and position shifts
over time. Incorporating these expanded datasets into the
treatment planning process has the potential to yield better
treatment plans, but at the same time results in models and
optimization problems that are several magnitudes larger than
those associated with traditional singletimeperiod planning.
And along with the increase in problem size, there are additional
sources of uncertainty and error (e.g., uncertainties in breathing
trajectories, errors in organ contour outlining related to
the increased number of images). Treatment planning methods
must therefore be developed that can accommodate the increased
problem size, and at the same time compensate for the errors
and uncertainties.
In this talk, we describe various mathematical models for
such robust and largescale planning methods. Their mathematical
complexity will be analyzed, and theoretical results will
be described. We will demonstrate that our methods allow a
reduction in mean dose to normal tissue, and in some cases,
higher dose to tumor volume.
and
Timothy Craig, Princess Margaret Hospital
Accuracy in Radiation Therapy: Current Achievements, Future
Solutions
Recent technical innovations in radiation therapy such as
intensity modulated radiation therapy (IMRT) and imageguided
radiation therapy (IGRT) provide the ability to deliver a
high dose of radiation that conforms to the shape of a tumour
while also avoiding healthy tissue. To ensure that the high
radiation dose is localized on the tumour, great accuracy
is required for treatment delivery. In addition, treatment
must be designed to be robust to residual uncertainties in
the treatment process.
This talk will briefly introduce the basics of radiation
therapy and highlight some of the recent developments and
technical challenges in patient care taking place at Princess
Margaret Hospital.




