2016 INFORMS Annual Meeting Program

419 / 561

INFORMS Nashville – 2016
419
WB68
Mockingbird 4- Omni
Spatiotemporal Data based Quality Control Methods
in Manufacturing
Sponsored: Quality, Statistics and Reliability
Sponsored Session
Chair: Mohammed Saeed Shafae, Virginia Tech, 112 Durham Hall, 1145
Perry Street, Blacksburg, VA, 24061, United States,
Co-Chair: Lee Wells, Assistant Professor, Western Michigan University,
E-208 Floyd Hall, 1903 W Michigan Ave, Kalamazoo, MI, 49008,
United States,
1 - Spatial Discrete Model For Clustered Defects On Wafer Maps
Hao Wang, Tsinghua University,
Yield, which contributes to increase the process quality, is a key concern in the
fabrication of semiconductor wafers. In this paper, we propose a novel discrete
spatial model based on discrete spatial defects data on wafer maps for analyzing
and predicting the yields at different chip locations. Based on the Bayesian
framework, we adopt a generalized linear model that considers both the spatial
coordinates and random spatial error, thereby significantly improving the
performance of the model. The experimental results show that the generalized
linear Poisson model that considers both the spatial coordinates and random
spatial error offers an improved fit to spatially correlated wafer map data.
2 - Spatial Models In Metal Additive Manufacturing
Bianca Maria Colosimo, Politecnico di Milano, Milano, Italy,
Marco Grasso
Additive manufacturing is more and more often moving from prototyping to
production and this is why new methods and tools for quality inspection and
monitoring are needed. In order to model shapes and internal defects, spatial
models can be used. This talk shows how spatial modeling can be used to model
complex shapes and internal defects (e.g., porosity) in metal additive
manufactured products.
3 - Reduced-dimension Mcusum Chart For
Spatio-temporal Surveillance
Junzhuo Chen, Georgia Institute of Technology, Atlanta, GA,
United States, Seong-Hee Kim, Yao Xie
In spatiotemporal surveillance, control chart with scan statistics is a powerful
method. Usually calculating monitoring statistic requires observations from the
whole monitoring area and the full covariance matrix inversion. However, if the
dimensionality is high, implementation can be challenging. First, it is hard to
estimate the full covariance matrix. Second, the computation of matrix inversion
is expensive. Finally, collecting data from all the sensors may be costly. To address
such issues, we propose the Reduced-Dimension MCUSUM chart that constructs
the monitoring statistic using measurements from a small group of locations. We
conduct simulations to study performance of the method.
WB69
Old Hickory- Omni
Network Design and Optimization
Sponsored: Telecommunications
Sponsored Session
Chair: Richard Li-Yang Chen, Sandia National Laboratories, 7011 East
Ave, Livermore, CA, 94550, United States,
1 - Modulation Design For MIMO HARQ Channel
Hans Mittelmann, Arizona State University,
Wenhao Wu, Zhi Ding
Modulation diversity (MoDiv) is a simple and practical transmission enhancement
technique that utilizes different modulation mappings to reduce packet loss rate
and achieve higher link throughput. MoDiv is particularly meaningful and
effective in hybrid-ARQ systems. We study the deployment and optimization of
MoDiv for HARQ in a MIMO-coordinated multi-point (MIMO-CoMP) scenario to
mitigate packet loss. We formulate the design optimization of MoDiv into a
quadratic three-dimensional assignment problem (Q3AP), then solve it using a
modified iterated local search (ILS) method. Numerical results demonstrate clear
performance gain over simple retransmissions and over a heuristic design.
2 - A Robust Optimization Approach For Network Interdiction
Amelia Musselman, Georgia Institute of Technology, Atlanta, GA,
United States, , Richard Li-Yang Chen,
Janson Wu
Networks arise in many systems that play an integral role in our daily lives, from
the internet to the national electric grid. It is important to protect these networks
from potential attacks. However, oftentimes the budget for network security is
limited, and the effectiveness of various defense mechanisms may be uncertain.
In this research we develop a robust optimization algorithm for selecting defense
options to strengthen network security with a limited budget. We use a bi-level
programming model, where the adversary’s goal is to maximize damage to the
system while the defender’s goal is to minimize this damage. We test our method
on a large synthetic problem of the U.S. supply chain network.
WB70
Acoustic- Omni
Transportation, Ops II
Contributed Session
Chair: Antoine Petit, U of Illinois at Urbana-Champaign, 205 N
Mathews Avenue, # B156, Urbana, IL, 61801, United States,
1 - Travel Time Estimation Based On Complex Networks Within
A DTA Framework
Rui Chen, Tsinghua University, Shunde building of Tsinghua
University, Beijing, China, Satish Ukkusuri
Data-driven estimation based on complex networks is a most important one of
new methods which could deal with DTA for both associated mathmatical
properties and computational ability. Therefore, we proposed a data-driven travel
time estimation model based on Complex Networks within a DTA framework.
2 - System Optimal Traffic Signal Control Under Dynamic
User Equilibrium
Rui Ma, Postdoc Scholar, University of California, Davis,
1001 Ghausi Hall, One, Davis, CA, 95616, United States,
, Hao Yu, Michael Zhang
Dynamic user equilibrium (UE) introduces nonlinear constraints with time-
varying state-dependent delay terms. An optimal traffic signal control framework
is proposed to find the signal control settings that minimize the total travel time in
a road network, as well as maintaining the UE condition and other realistic
spillback constraints. In this study, a heuristic solution method is proposed to
solve the nonlinear problem with time-varying, state-dependent delays. The
resulting solution satisfies the desired properties, which suggests the proposed
solution algorithm is better than the previous introduced method with
approximation by constant time delays.
3 - Managing The Daily Operations Of A Bike Sharing System Using
Portable Stations
Rahul Swamy, PhD Student, University of Illinois Urbana-
Champaign, Champaign, IL, 61820, United States,
, Jose Luis Walteros
This research aims to provide an integrated mathematical framework for
operating a bike-sharing system using portable stations. We propose solving a
sequence of MILPs to optimally determine the locations of portable stations across
a time period in order to minimize redistribution logistics. A Bender’s
decomposition based solution strategy is presented. Existing work in this area
treat this problem separate from the bike station location problem. We propose an
integrated approach.
4 - The Impact Of Demand Uncertainty On Subsidy Design In
BOT Road Projects
Zhuo Feng, Dalian University of Technology, No. 2 Linggong Road,
Dalian, 116024, China, , Yiwen Zhang
The private investor faces substantial demand uncertainty in BOT (Build-Operate-
Transfer) road projects, which depresses her participation. To attract private
investors, the government often offers subsidies in some BOT road projects. In
this paper, we will mainly consider usage-based subsidy. We first examine the
impact of demand uncertainty on the government’s subsidy design by considering
the private investor’s response in designing toll price and road capacity. We
further make two extensions by locating the project in a road network and by
considering the private investor’s information advantage of her operating cost,
respectively.
WB70