2016 INFORMS Annual Meeting Program

438 / 561

INFORMS Nashville – 2016
438
4 - Cardinality Constrainted CDS Portfolio Optimization
Dexiang Wu, Stockholm University, Stockholm Business School,
Stockholm, 106 91, Sweden, ,
Desheng Dash Wu
We study the Credit Default Swap (CDS) market from the portfolio perspective.
CDS-based portfolios are constructed through incorporating solvency and
cardinality constraints for the purpose of decentralization. Portfolio size is
controlled exactly and therefore mixed integer quadratic and linear programs that
consider different risk measurements are studied. We found that moderate size
can generally obtain better performance in terms of portfolio Sharpe ratio and
other metrics. Moreover, due to the specific structure of CDS correlation matrix, a
cluster simplification process is applied to speed up the computation.
WC33
203B-MCC
Production and Scheduling III
Contributed Session
Chair: Steffen T. Klosterhalfen, BASF SE, Ludwigshafen, Germany,
1 - Fitting Clearing Fun Actions Using Generalized
Regression Methods
Reha Uzsoy, North Carolina State University, Dept. of Industrial &
Systems Engg, 300 Daniels Hall Camps Box 7906, Raleigh, NC,
27695-7906, United States, ,
Karthick Gopalswamy
Clearing functions are widely used in production planning models to capture the
nonlinear relationship between workload and output. Traditionally least squares
methods have been used to fir the data, which weight the errors of both signs
equally and assume errors to be iid normally distributed. In this work we relax
the assumption of normality and provide a generalized regression approach to fit
the data taking into consideration that the data is not balanced. Computational
experiments evaluate the performance of the proposed methods for fitting
clearing functions.
2 - A Two-stage Stochastic Programming Model For Lot-sizing And
Scheduling Under Uncertainty
Zhengyang Hu, Research Assistant, Iowa State University,
100 Enrollment Services Center Ames, Ames, IA, 50011,
United States, Guiping Hu
Lot-sizing and scheduling is one of the medium-term production planning
problems in manufacturing. In this study, demand uncertainty has been
considered and a robust production plan has been proposed with a two-stage
stochastic programming framework. A case study proves that uncertainty has a
significant impact on production planning.
3 - Managing Product Transitions In Semiconductor Wafer
Fabrication Facilities
Reha Uzsoy, North Carolina State University, Dept. of Industrial &
Systems Engg, 300 Daniels Hall Camps Box 7906, Raleigh, NC,
27695-7906, United States, , Atchyuta B. Manda,
Sukgon Kim, Karl Kempf
We consider the problem of managing the introduction of new products into a
wafer fabrication facility when the new product is subject to higher levels of
process uncertainty than the current one. We propose a model for the impact of
the new product on the cycle time of the fab using queueing concepts, and
illustrate the behavior of the model with computational experiments.
4 - Scheduling With Batching Decisions And Energy Constraints For
Steelmaking Continuous Casting Production
Wenjie Xu, Northeastern University, NO. 3-11, Wenhua Road,
Heping, Shenyang, 110819, China,
Lixin Tang
We study a novel scheduling problem with batching decisions of steelmaking
continuous- casting (SCC) production. The energy constraints in this problem
represent the conversion process from the Linz-Donawitz process gas (LDG) to
electricity. The problem uses the minimum makespan as the scheduling objective
and the minimum total electricity cost as the energy objective. A multi-objective
optimization framework which incorporates an improved epsilon-constraint
method is proposed to solve the problem. Preliminary results show the
effectiveness of the multi-objective optimization framework and demonstrate the
tradeoffs between minimum makespan and energy cost.
5 - Integrated Production And Safety Stock Planning In The
Process Industry
Steffen T. Klosterhalfen, BASF SE, Ludwigshafen, Germany,
Stefan Minner,
Dariush Tavaghof Gigloo
We develop and apply a new approach for integrated production lot-sizing and
safety stock planning in the process industry where high demand uncertainty and
large production campaigns are the rule. Our approach is based on mixed-integer
linear programming and benchmarked with common sequential lot-sizing and
safety stock planning frameworks characterized by different levels of
sophistication in optimization methodology and parameter updating.
WC34
204-MCC
Joint Session HAS/MSOM-HC: Advances in
Healthcare Operations
Sponsored: Manufacturing & Service Oper Mgmt,
Healthcare Operations
Sponsored Session
Chair: Van-Anh Truong, Columbia University, 500 120th Street,
New York, NY, 10027, United States,
1 - A Pomdp For Reducing Readmissions Through Inpatient
Outpatient Joint Control
Xiang Liu, University of Michigan, ,
Jonathan Helm, Mariel Sofia Lavieri, Ted Skolarus
Hospital readmissions affect hundreds of thousands of patients, placing a
tremendous burden on the healthcare system. We develop a two-stage POMDP
that spans the inpatient stay and the post-discharge outpatient monitoring to
reduce readmission. By learning and reducing readmission risk in the inpatient
stage, and monitoring and intervening patient’s health condition in the second
stage, our model jointly optimizes both discharge and post-discharge decisions to
reduce readmissions.
2 - A Fluid Model For An Overloaded Bipartite Queueing System With
Scoring Based Priority Rules
Yichuan Ding, Assistant Professor, University of British Columbia,
2053 Main Mall, Vancouver, BC, V6T1Z2, Canada,
Mahesh Nagarajan,
S. Thomas McCormick
We consider an overloaded bipartite queueing system (BQS) with multi-type
customers and service providers. A service provider assigns each customer a score
based on customer type, waiting time, and server type. Service is always provided
to the customer with the highest score. We approximate the behavior of such a
system using a fluid limit process, which has two important features: (1) the
routing flow rates at a transient state coincide with the maximal flow in a
parameterized network; (2) the routing flow rates in the steady state coincide
with the minimal-cost maximal-flow in a capacitated network. We illustrate the
application of our machinery via an example of public housing assignment.
3 - Routing Shared Vehicles With Matching Constraints For Medical
Home Care Delivery
Miao Yu, University of Michigan, 1205 Beal Avenue, Ann Arbor,
MI, 48109, United States, ,
Viswanath Nagarajan, Siqian Shen
In this paper, we study a vehicle routing problem variant for medical home care
delivery. A health care provider assigns multiple vehicles to transport homecare
devices and/or medical staff to patients’ home locations given that each patient
can only be served by a subset of vehicles. We construct an integer-programming
model solved by column generation, to minimize the total traveling distance of all
the vehicles. We also propose an approximation algorithm that yields fast
assignment, and conduct out-of-sample simulation to numerically evaluate the
performance of the proposed methods.
4 - A Periodic Little’s Law And Its Application To Emergency
Department Data
Xiaopei Zhang, Columbia University, 1 Morningside Drive, Apt.
1710, New York, NY, 10025, United States,
Ward Whitt
We establish a new periodic discrete-time version of Little’s law and apply it to
explain the remarkable fit of a data-driven stochastic process model, which is
periodic over a week, of the emergency department occupancy over time in the
Israeli Rambam hospital.
WC33