Informs 2015

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INFORMS Philadelphia – 2015
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4 - Initiative Scheduling Mode for Physical Internet-based
Manufacturing System
Jun-Qiang Wang, Professor, Northwestern Polytechnical
University, Box 554, No. 127 West Youyi Road,
Department of Industrial Engineering, Xi’an, 710072, China,
Guo-qiang Fan, Shu-dong Sun,
Ying-feng Zhang
We categorize scheduling as passive scheduling and initiative scheduling,
depending on who takes the initiative and controls the decision-making of
scheduling in physical internet-based manufacturing systems. Focusing on
initiative scheduling mode, we model a p-shaped framework for scheduling
elements, analyze the decentralized operation mode, explore the individual and
organizational scheduling behaviors among enabling units. Finally we discuss
some future research directions.
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76-Room 204C, CC
Design of Experiments and Statistical Analysis
for Simulation
Sponsor: Simulation
Sponsored Session
Chair: Feng Yang, Associate Professor, West Virginia University, P.O.Box
6070, Morgantown, United States of America,
Co-Chair: Hong Wan, Associate Professor, Purdue University, 315 N.
Grant Street, GRIS 327, West Lafayette, United States of America,
1 - Simulation Experiments Involving Stochastic Optimization Models
for Disaster Relief
Susan Sanchez, Professor, Naval Postgraduate School, Operations
Research Dept, 1411 Cunningham Rd, Monterey, CA, 93943,
United States of America, , Emily Craparo,
Maxine Gardner
Stochastic optimization approaches have been used for determining effective
disaster relief operations, but may not fully capture the uncertainty that is
inherent in these disasters and the demands that result. We use large-scale design
of experiments to more fully investigate the effect of variability on the solution of
a two-stage mixed-integer stochastic optimization model that explores using UAVs
as logistics assets when planning the Navy’s logistics response to natural disasters.
2 - Sequential Experimental Designs for Stochastic Kriging
Xi Chen, Assistant Professor, Industrial and Systems Egnineering
at Virginia Tech, 1145 Perry St., Blacksburg, VA, 24061,
United States of America,
In this work, we establish a sequential experimental design framework for
applying Stochastic Kriging (SK) to predicting performance measures of complex
stochastic systems. We show how the integrated mean squared error of prediction
decreases as additional simulation runs are allocated sequentially, and derive
some efficient sequential design strategies from these analytic results. The
performance of the proposed sequential design strategies is demonstrated through
numerical examples.
3 - Block-coordinate Strong for Large Scale Simulation Optimization
Hong Wan, Associate Professor, Purdue University, 315 N. Grant
Street, GRIS 327, West Lafayette, United States of America,
, Wenyu Wang
STRONG is a response surface methodology (RSM) based algorithm that
iteratively constructs linear or quadratic fitness model to guide the searching
direction within the trust region. For high-dimensional problem, this paper
modify the Block Coordinate Descent framework to fit the STRONG algorithm,
and propose an algorithm which guarantees to converge to a stationary point.
This is the first result establishing the BCD framework in high dimensional
simulation optimization problems.
SC77
77-Room 300, CC
Supply Chain Management III
Contributed Session
Chair: Pengyu Chen, PhD Student, Huazhong University of Science
&Technology, 1037 Luoyu Road, Wuhan, China,
1 - Control and Emergence in Supply Networks
Anand Nair, Michigan State University, 632 Bogue St.,
East Lansing, MI, United States of America,
Ilaria Giannoccaro, Thomas Choi
In this paper we consider the supply network of Honda as the focal firm and
develop an empirically-informed NK simulation model to examine how varying
levels of control influence performance of supply networks.
2 - A Study on Internet of Things and Supply Chain Agility
Bo Li, Ashland University, 401 College Ave, Ashland, OH,
United States of America,
Internet of Things (IoT) changes our daily life and business world, thus supply
chain managers must answer the question about how IoT can improve their
supply chain performances. This research develops a conceptual model with
simulation demonstration, to study the relationship among IoT, supply chain
agility, and supply chain performances.
3 - Orders and Reciprocity in the Technology Supply Chain
Heejong Lim, Purdue University, 403 W. State Street, West
Lafayette, IN, United States of America, ,
Ananth Iyer
Motivated by the semiconductor and the LCD industry, we incorporate the
reciprocal game in a dyadic (buyer-supplier) supply channel. In our model, the
buyer’s anticipated reciprocal behavior influences the seller’s order so as to protect
the seller during the oversupply period. We provide an analysis under different
level of reciprocity following accepted economic models in order to explore the
impact on order size and channel coordination. Insights from practice are then
provided.
4 - Vertical Integration in Two-tier Decentralized Supply Chain
Pengyu Chen, PhD Student, Huazhong University of Science
&Technology, 1037 Luoyu Road, Wuhan, China,
, He Xu
We study a supply chain with three types of firms (i.e. suppliers, manufacturers
and integrated firms). Integrated firms can sell parts and final products while
suppliers and manufacturers can sell only one of them. We find the conditions
under which integrated firms sell parts to other manufacturers and investigate
how prices and social wealths are affected. We also answer the question when
two individual firms prefer to vertically merging.
SC78
78-Room 301, CC
Supply Chain Risk Management I
Contributed Session
Chair: Lisa Yeo, Assistant Professor, Loyola University Maryland, 4501
N. Charles St., Sellinger Hall 306, Baltimore, MD, 21210, United States
of America,
1 - Perspectives on Supply Chain Corruption and Risk Management
Xiaojing Liu, PhD Candidate, The University of Auckland, 12
Grafton Road, Auckland City, Auckland, 1010, New Zealand,
Tiru Arthanari
Research on supply chain risk management is still immature and of increasing
importance. Corruption from the perspective of supply chains largely lacks
research. We propose a conceptual framework for managing corruption risk in
supply chains. Case studies help verify and establish factors. System dynamics
modelling clarifies complex relationships. We anticipate exploring how corruption
risks modify supply chain risk factors and performance, and how to safeguard
supply chains against such risks.
2 - An Examination of the Impact Supplier Flexibility and Reliability
on Supply Chain Resilience
Masoud Kamalahmadi, Student, North Carolina A&T State
University, 1601 E. Market St, Greensboro, NC, 27411, United
States of America,
Mahour Mellat Parast
In this paper, the impact of supplier flexibility and reliability on supply chain
resilience is examined. We develop a mathematical model to minimize the impact
of two types of supply chain disruptions (supply disruption and environmental
disruption), and propose strategies for supplier selection and allocation to
minimize supply chain risks and costs. Risk of delivery reliability is also examined
in this study.
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