52 ISE Magazine | www.iise.org/ISEmagazine
Inside IISE Journals
To explore, or not to explore:
That is the question in running digital twins
Exploration versus replication (or exploitation) has been a
constant struggle whenever global optimization is desired,
but the response surface is complex. Consider the multi-
armed bandit problem, a kind of sequential decision-mak-
ing problem that investigates whether the decision-maker
should move to another arm (exploration) or stick to the
current arm (replication) to minimize regret.
A similar issue arises when running digital twins, a vir-
tual representation of a real physical process or system. As
a part of the emerging trend of using digital technologies,
digital twins play a crucial role for monitoring and testing
the performance of actual systems in many applications.
In their article “Optimal Budget Allocation for Stochas-
tic Simulation With Importance Sampling: Exploration vs.
Replication,” professor Young Myoung Ko from Pohang
University of Science and Technology and professor Eun-
shin Byon from the University of Michigan discuss how
to strike a balance between exploration and replication for
effectively running digital twins.
Running a digital twin often takes a two-level simu-
lation procedure in which the first level simulates a sys-
tems operating conditions and the second level invokes a
stochastic black-box computer model. Such procedure has
been widely used, including in renewable energy systems
and financial engineering. Almost always, the bottleneck is
the limited computational resource, in particular when the
black-box computer model is computationally demanding.
Variance reduction techniques, such as importance sam-
pling, help reduce the computational budget requirement,
but they do not provide a general guideline on whether to
explore or replicate, i.e., whether to run simulations at new
operating conditions or replicate at already sampled condi-
tions to further exploit the stochastic output.
The authors show that simulation schemes that allow
both exploration and replication theoretically provide an
optimal trade-off, but the optimal strategy easily becomes
impractical to implement because it requires a noninte-
This month we highlight two articles in IISE Transactions. The first article looks into how to effectively run digital twins
for monitoring and performance testing of actual physical systems. Specifically, the question is whether one would be
better off spending more resources exploring new input conditions or spending those resources exploiting the current
input condition. The authors found that an exploration-only scheme will do just fine. They demonstrate the merit of their
exploration-only approach using the National Renewable Energy Laboratory’s wind turbine simulator. The second article
attempts to provide an understanding of how flexibility enables better economic decisions in power system planning
expansion. Such understanding is provided by a set of decision rules solved through optimizing the time-based deployment
of a portfolio of generators that meet future energy demands at the lowest possible cost. Using a real-world power
generation expansion problem in the Midwestern United States, the authors show that flexibility brings significant cost
savings to complex energy systems design and planning. These articles will appear in the September 2022 issue of IISE
Transactions (Volume 54, No. 9).
Young Myoung Ko Eunshin Byon
August 2022 | ISE Magazine 53
ger number of simulation runs. To tackle the issue, they
propose an alternative scheme that does only exploration
and no replication. They prove that the exploration-only
scheme guarantees lower variance than the implementable
version of the theoretically optimal exploration-and-repli-
cation scheme.
A case study using the National Renewable Energy
Laboratory’s wind turbine simulator demonstrates that the
exploration-only simulation performs well and generates
robust results. The results provide critical insights for, as
well as practical guidelines in, using digital twins for trans-
forming system design and operations.
CONTACT: Eunshin Byon; ebyon@umich.edu; Industrial and Opera-
tions Engineering Department, University of Michigan, 1205 Beal Ave.,
Ann Arbor, MI 48109 and Young Myoung Ko; youngko@postech.ac.kr;
Department of Industrial and Management Engineering, Pohang Uni-
versity of Science and Technology, 77, Cheongam-ro, Nam-gu, Pohang,
Gyeongbuk, 37673, South Korea
Rethinking power systems expansion
planning: How flexibility enables
better economic decisions and
sustainability in the face of uncertainty
As the world shifts toward environmentally friendlier
power generation systems
to fight climate change in
more sustainable ways, the
intermittence of renewable
energy sources such as wind
and solar is becoming a cru-
cial contributor of uncer-
tainty, especially in meet-
ing ever-increasing energy
Making timely invest-
ments for long-term nation-
al grid expansion of gen-
eration capacities requires careful planning and flexibility
to adapt to constantly changing conditions. Flexibility in
design is a paradigm derived from the theory of real op-
tions. It moves away from standard design approaches by
focusing on complex energy system designs that shift the
distribution of possible outcomes (e.g., net present value,
costs) toward better outcomes while reducing exposure to
downside risks.
In the article “Flexibility and Real Options Analysis in
Power System Generation Expansion Planning Under Un-
certainty,” Aakil Caunhye, lecturer and assistant professor
Aakil Caunhye
IISE publishes four peer-reviewed re-
search journals that address key topics
in the industrial and systems engineer-
ing world. Summaries from various is-
sues are featured in the Research sec-
tion each month in ISE. For information
on how to subscribe or submit articles,
visit iise.org/publications.
IISE Transactions (link.iise.org/iise-
transactions) is IISE’s flagship research
journal and is published monthly. It aims to foster exchange
among researchers and practitioners in the industrial engi-
neering community by publishing papers that are grounded
in science and mathematics and motivated by engineering
IISE Transactions on Healthcare Systems Engineering (link.
iise.org/iisetransactions_healthcare) is a quarterly, refereed
journal that publishes papers about the application of indus-
trial engineering tools and techniques to healthcare systems.
The Engineering Economist (link.iise.org/engineeringecono-
mist) is a quarterly refereed journal published jointly by IISE
and the American Society of Engineering Education. Devoted
to issues of capital investment, its topics include economic
decision analysis, capital investment analysis, research and
development decisions, cost estimating and accounting, and
public policy analysis.
IISE Transactions on Occupational Ergonomics and Human
Factors (link.iise.org/iisetransactions_ergonomics) is de-
voted to compiling and disseminating knowledge on occu-
pational ergonomics and human factors theory, technology,
application and practice across diverse areas. You can follow
on Twitter at twitter.com/iisetoehf or @iisetoehf.
About the journals
54 ISE Magazine | www.iise.org/ISEmagazine
of business analytics at The University of Edinburgh Busi-
ness School; Michel-Alexandre Cardin, senior lecturer and
associate professor in computational aided engineering at
Imperial College London; and former National University
of Singapore undergraduate student Muhammad Rahmat,
now at the Ministry of Trade and Industry Singapore, in-
troduce an intuitive approach to optimize deployment of
power generation systems that allow better flexibility, eco-
nomic performance and sustainability under renewable en-
ergy supply uncertainty.
Their work proposes a new mathematical model that op-
timizes the time-based deployment of a portfolio of genera-
tors to meet future energy demands at the lowest possible
cost. Embedded in the model is a set of decision rules that
allow the conditional adaptation of generator deployment
as uncertainty evolves over time. This deploys capacity only
if and when it is needed, thus contributing to better sus-
tainability. These rules are based on optimized thresholds
from historical observations of the capacities of intermittent
energy sources and allow a portfolio of generators to be de-
ployed only when those capacities fall below the thresholds.
The decision-making framework is demonstrated on the
analysis of a real-world power generation expansion prob-
lem in the U.S. Midwest. The authors show that flexibility
brings significant cost savings to complex energy systems
design and planning. This contributes to making better use
of limited economic resources while improving the sustain-
ability of future renewable energy systems.
CONTACT: Michel-Alexandre Cardin; m.cardin@imperial.ac.uk; Dyson
School of Design Engineering, Imperial College London, UK
Yu Ding is the Mike and Sugar Barnes Professor of Industrial
and Systems Engineering at Texas A&M University and Associ-
ate Director for Research Engagement at the Texas A&M Institute
of Data Science. He is editor-in-chief of IISE Transactions and a
fellow of IISE.
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On-campus, online
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Systems Science and
Industrial Engineering at
Binghamton University
Systems Science and Industrial Engineering
SUNY Distinguished
track faculty
SUNY Chancellors
Award recipients
in research
in 2020–21
in Industrial and
Systems Engineering
(BS, MS, PhD), Systems
Science (MS, PhD) and
Healthcare Systems
Engineering (MS)
doctoral students
Michel-Alexandre Cardin Muhammad Rahmat