2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
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3 - Parallel Computing For The Optimization Of A Large-scale
Dynamic Network - The Internet Of Hearts
Chen Kan, Pennsylvania State University, University Park, PA,
16802, United States, Hui Yang
Rapid advancements of mobile computing provide an unprecedented opportunity
to empower a next generation mobile health system - the internet of heart (IoH).
The IoH embeds patients into a dynamic network and reveals the change of
patient’s status through network variations. However, it poses a great challenge
for real-time recognition of disease patterns when large number of patients are
involved in IoH. This study develops a novel scheme to optimize the network in a
parallel, distributed manner, thereby improving the the efficiency of computation.
Experimental results show that the developed scheme is effective and efficient for
realizing smart connected healthcare in large-scale IoH contexts.
4 - Control Policies For Iot Manufacturing Systems: A Two Stage
Stochastic Approach
Xu Jin, Texas A&M University, College Station, TX, United States,
, Natarajan Gautam, Satish Bukkapatnam,
Hoang Tran
We consider a smart manufacturing setting where materials and machines are
part of an IoT. A two-stage stochastic model is formulated to determine tool
replacement and processing speed decisions based on the availability of the job
arrival as well as machine health and processing status information. Stage 1 uses a
Lyapunov method to cluster jobs for throughput optimization, and Stage 2
employs a stochastic scheduling algorithm to minimize cycle times. We also
analyze the effectiveness of this approach using extensive numerical testing.
TD08
103A-MCC
Outsourcing Innovation
Invited: Business Model Innovation
Invited Session
Chair: Ersin Korpeoglu, University College London, London,
United Kingdom,
1 - Performance Feedback In Competitive Product Development
Daniel P Gross, Harvard Business School,
Performance feedback is ubiquitous in competitive settings where new products
are developed. This paper introduces a tension between incentives and
improvement in performance evaluation. Using a sample of four thousand
commercial logo design tournaments, I show that feedback reduces participation
but improves the quality of submissions, with an ambiguous effect on high-
quality output. To evaluate this tradeoff, I develop a procedure to estimate agents’
effort costs and simulate counterfactuals under alternative feedback policies. The
results suggest that feedback on net increases the number of high-quality ideas
produced and may thus be desirable for a principal seeking innovation.
2 - Workforce Mobility And Innovation Outcomes In Manufacturing
Philipp Cornelius, University College London, London,
United Kingdom, , Bilal Gokpinar,
Fabian Sting
Employee ideas are a valuable starting point to improve operational efficiency. We
empirically investigate how moves between problems and sites affect the
innovation value created by employee ideas for the organization. We document
that the dynamic effects of problem switches differ fundamentally from the effects
of site switches: The innovation outcomes of problem switching employees follow
a concave inverse u-shaped pattern, whereas the innovation outcomes of site
switching employees follow a convex u-shaped pattern over time. We discuss
implications for theory.
3 - Contest Among Contest Organizers
Ersin Korpeoglu, School of Management, University College
London, London, United Kingdom, ,
Isa E Hafalir
This paper analyzes the organization of multiple innovation contests in which
organizers post problems to a group of agents, and elicit innovative solutions. We
compare the contest organizers’ payoffs when they organize multiple contests
simultaneously or when they compete with other contest organizers for the effort
of agents towards solving their problems. We show that depending on problem
structure, more intense competition among organizers and organizing multiple
contests may harm or, counter-intuitively, benefit each organizer. Our findings
explain why organizers find it beneficial to hold multiple contests or organize
similar contests with their competitors simultaneously.
TD09
103B-MCC
Big Data II
Contributed Session
Chair: Haibo Wang, Killam Distinguished Associate Professor, Texas
A&M International University, 5201 University Boulevard, Laredo, TX,
78045, United States,
1 - Integrating Data Science In Statistical Practice And Analytics
Steven B Cohen, RTI International, 701 13th Street NW,
Washington, DC, 20005, United States,
The field of data science has served to rapidly expand the knowledge base and
decision-making ability through the combination of seemly disparate and diverse
sources of information and content, which include survey and administrative
data, social, financial and economic micro-data, and content from mobile devices,
the internet and social media. Other attributes of data science include data
visualization; predictive, mathematical and simulation modeling; use of Bayesian
methods, machine learning; GIS and geospatial analytics and Big Data
technologies. In this presentation, attention is given to demonstrate the capacity
of data science to enhance study designs and predictive analytics.
2 - Next-generation Sequencing (NGS) Data Analysis:
Developing A Scalable Framework For The Future
Michael Chuang, State University of New York, 1 Hawk Drive,
New Paltz, NY, 12561, United States,
NGS analysis presents a domain for biomedical and information technology
professionals to explore. Due to the large amount of data involved and various
constraints of technologies, we delineate issues to consider to develop a
framework using parallel computing and NoSQL database service to greatly
reduce the required time under less infrastructure investments while achieving
satisfactory accuracy.
3 - Five Steps To Big Data Analytics
Xuan Wang, PhD Student, Louisiana State University, 2200
Business Education Complex, Nicholson Extension, Baton Rouge,
LA, 70803, United States, Helmut Schneider
Analytics has been categorized as descriptive, predictive and prescriptive.
However, much many challenges lie in the data preparation. Also, analytics is
typically concerned about prediction rather than explaining, leaving manager’s to
question whether to trust results. Hence, data preparation and causal inference
are two important steps in analytics at the beginning and end of an analytics
project life cycle.
4 - Prescriptive Analytic For Public Transportation Corridor Planning
Haibo Wang, Killam Distinguished Associate Professor, Texas A&M
International University, 5201 University Boulevard, Laredo, TX,
78045, United States, , Wei Wang, Jun Huang
We investigate how public transportation planning affects the economic growth
and social development in the urban areas, especially the economic enhancement
zones in US cities. We build visualization tools to help decision makers
understand the impact of future planning and issues of existing system.
TD10
103C-MCC
Optimization in Renewable Energy
Sponsored: Energy, Natural Res & the Environment, Energy II Other
Sponsored Session
Chair: Sushil Raj Poudel, MSU, MSU, Starkville, MS, 39760,
United States,
1 - Sustainable Network Design For Multi-purpose Pallet Processing
Depots Under Biomass Supply Uncertainty
MD Abdul Quddus, PhD Student, Mississippi State University,
Department of Industrial & Systems Engineering, P.O. Box 9542,
Starkville, MS, 39762, United States, , Niamat
Ullah Ibne Hossain, Mohammad Marufuzzaman, Raed Jaradat
This study develops a two-stage stochastic mixed-integer programming model to
manage sustainable pellet processing depots under feedstock supply uncertainty.
The proposed optimization model not only minimizes cost but also mitigates
emissions from the supply chain network. We develop a hybrid decomposition
algorithm that combine Sample average approximation with an enhanced
Progressive Hedging (PH) algorithm. Mississippi and Alabama are selected for
testing ground of this model. The results of the analysis reveal promising insights
that could lead to recommendations to help decision makers to achieve a more
cost-effective environmentally-friendly supply chain network.
TD08