52 ISE Magazine | www.iise.org/ISEmagazine
Inside IISE Journals
research
Ample supplies of diesel fuel
drive hurricane relief work
Since 2005 when history’s costliest storm, Hurricane Ka-
trina, made landfall in Louisiana, Category 4 and 5 hurri-
canes have caused more than $600 billion in damage in the
U.S. and the Caribbean. Hurricanes in the coming century
will likely be more intense, bring more rainfall and cause
greater coastal inundation.
How do we mitigate damage from future hurricanes? So-
lutions include curbing global warming, building resilient
coastal infrastructure and preserving coral reefs to prepar-
ing for relief and recovery operations.
In “Optimizing Diesel Fuel Supply Chain Operations to
Mitigate Power Outages for Hurricane Relief,” Haoxiang
This month we highlight two articles in IISE Transactions. The first article focuses on the issue of diesel fuel supply chain
in the context of hurricane relief. It plays an important role in evacuation, repair and emergency power generation when a
major natural disaster strikes. The authors developed an adaptive strategy using a two-stage stochastic optimization model.
They conducted a retrospective analysis using data from 2017 Hurricane Irma in Florida and found that the proposed
stochastic optimization-based method can help reduce unmet surge demand by 9%, about 15,000 barrels of diesel fuels.
The authors of the second article argue that the new stars of the stock markets, e-commerce retailers such as Amazon, can
still learn from car manufacturers when it comes to product-to-order-assignment in warehouses. The answer is to apply late
order assignment. The authors show that e-commerce retailers can successfully borrow the idea of late order assignment
to speed up the sortation processes in their consolidation areas, which provides significant throughput gains and avoids
requiring additional consolidation areas. These articles will appear in the October 2022 issue of IISE Transactions (Volume
54, No. 10).
.
Researchers, from left, Haoxiang Yang, Thomas Massion, Daniel Duque and David Morton.
September 2022 | ISE Magazine 53
Yang from the Chinese University of Hong Kong, Shen-
zhen; Daniel Duque from Google Research; and David
Morton from Northwestern University, with the assistance
of Thomas Massion from Northwestern, focus on relief op-
erations.
Earlier work on hurricane relief deals with evacuation,
rescue and distribution of supplies. The paper instead fo-
cuses on the diesel fuel supply chain using a case study from
Hurricane Irma in Florida in fall 2017. Diesel-fueled ve-
hicles are needed for evacuation and repair. Critical infra-
structure, such as hospitals, municipal water systems and
facilities for first responders, requires diesel for power gen-
eration when electricity is lost due to the hurricane.
During harsh weather conditions, including wind speeds,
what is the expected power loss? How does power loss cor-
respond to increased demand for diesel? To answer, the
paper’s predictive model uses data from Hurricane Irma.
Given multiple scenarios for an approaching hurricanes
path and intensity from the National Oceanic and Atmo-
spheric Administrations Global Ensemble Forecast System
(GEFS), how should we route tank trucks to deliver diesel?
The paper’s two-stage stochastic optimization model pre-
scribes answers to this question. NOAA updates projections
every three hours so the optimization model is continually
fed updated forecasts to guide dispatch of tank trucks from
terminal ports to deliver diesel throughout Florida.
A retrospective analysis of Hurricane Irma uses historical
weather forecasts and evaluates performance from observed
power outages. Using multiple scenarios from GEFS, it out-
performs a point forecast, reducing unmet surge demand
by 9%, or about 15,000 barrels. The paper’s framework is
designed to guide a state’s director of emergency manage-
ment, supported by officials from the Federal Emergency
Management Agency, who coordinate actions of the pri-
vate and government participants in diesel fuel operations.
CONTACT: Haoxiang Yang; yanghaoxiang@cuhk.edu.cn; +86-
18145801946; Daoyuan Building 417a, 2001 Longxiang Ave., Shenzhen,
Guangdong, China 518172
What e-commerce retailers can learn
from car manufacturing: Late order
assignment can be beneficial
Old, established car manufacturers who have been the stars
of the stock markets for decades are under increasing pres-
sure from new competitors these days. But in their paper,
“Efficient Order Consolidation in Warehouses: The Prod-
uct-To-Order-Assignment Problem in Warehouses with
Sortation Systems,” professor Nils Boysen, Konrad Stephan
and professor Felix Weidinger show that, once in a while,
the new stars of the stock markets – e-commerce retailers
such as Amazon – still can learn from car manufacturers.
To be flexible in reacting to disturbances such as miss-
ing parts, car manufacturers
apply late order assignment.
This means that during as-
sembly, they reassign spe-
cific cars to other customer
orders that demand all fea-
tures and have already been
assembled but do not re-
quire the missing parts. In
this way, assembly can pro-
ceed unaffected while rush
deliveries supply the miss-
ing parts. The German re-
searchers from the universities of Jena and Darmstadt show
that e-commerce retailers can successfully borrow the idea
of late order assignment to speed up the sortation processes
in their consolidation areas.
Most e-commerce retailers apply batching and zoning
in their picking areas to speed up manual order picking.
The price for this is an additional consolidation stage where
the products arriving from the picking area are sorted ac-
cording to customer orders. To ensure that all customer
demands are fullled, each picked product is assigned to
a specic customer order. The researchers, however, show
that once the picked products are placed on the conveyor
to be transported toward the consolidation area, a reassign-
ment can be beneficial, similar to the late order assignment
of car manufacturing.
Products that refer to the same stock keeping unit are in-
terchangeable among orders. Hence, they can be reassigned
to other orders, such that an order’s spread over the arrival
sequence on the conveyor is reduced. In this way, the time
an order occupies the sortation lanes of the fully automated
sortation conveyor is reduced. The paper introduces ef-
cient algorithms for this reassignment task and shows that
the late order assignment can provide significant through-
put gains in the consolidation area.
CONTACT: Nils Boysen; nils.boysen@uni-jena.de; Chair of Operations
Management, Friedrich Schiller University Jena, 07743 Jena, Germany
Nils Boysen Konrad Stephan
Felix Weidinger
54 ISE Magazine | www.iise.org/ISEmagazine
research
Can health beliefs predict
drowsy driving behavior?
Drowsy driving is prevalent among shift workers, especially
night-shift nurses. Despite the alarming rate of drowsy driving
crashes, there is a general gap in evidence-based approaches to
mitigate or prevent this dangerous behavior.
A research team, led by professors Anthony McDonald and
Farzan Sasangohar and Ph.D. candidates Karim Zahed and
Alec Smith from Texas A&M University, has been explor-
ing various technological, educational and behavioral inter-
ventions to address this challenge. In their paper, “The Ef-
fects of Drowsiness Detection Technology and Education on
Nurses’ Beliefs and Attitudes Towards Drowsy Driving,” they
reported a naturalistic driving experiment to investigate how
behavioral constructs such as beliefs and attitudes may affect
nurses’ intention to avoid drowsy driving.
Forty-four night-shift nurses recruited from a large hospital
in Texas were randomly assigned to three groups: 1) control; 2)
those who received an educational intervention; and 3) those
who received the same educational intervention tother with
in-vehicle drowsy detection technology. Their work utilized
an integrated model drawing from the constructs of the The-
ory of Planned Behavior and the Health Belief Model to elicit
attitudes, beliefs and intentions to avoid drowsy driving. Each
group was surveyed before exposure to the intervention(s) and
after the end of study to assess changes in their beliefs and at-
titudes. A path analysis model was used to model relationships
between beliefs and intention.
Their findings suggest that intention was predicted primar-
ily by attitude and the perceived health threat. The perceived
health threats also mediated the relationship between behav-
ioral intention and the influence of subjective norms, as well
as perceived behavioral control. Further, participants who re-
ceived education about drowsy driving had positive changes in
beliefs compared to the control group.
This study provides evidence that nurses’ perceived health
threat from driving drowsy and their initial attitude toward
interventions may serve as important indicators of the success
of drowsy driving interventions. Simple interventions that aim
at raising awareness of the risks associated with drowsy driving
may be an effective way of influencing nurses’ beliefs regard-
ing drowsy driving and positively impact their behavior.
CONTACT: Farzan Sasangohar; 3131 TAMU, College Station, TX 77843
How can practical human factors
and ergonomics knowledge be transferred
effectively to an organization?
Human factors/ergonomics (HFE) knowledge transfer is es-
sential for improving human-centered work, productivity
and generally improving work systems. For these purposes,
a participatory ergonomics process is recognized as a success-
ful strategy and a bottom-up intervention in transferring HFE
knowledge, both in industrialized countries and industrially
developing countries.
In their recent paper, Nosrat Abdollahpour from Tabriz
University of Medical Sciences in Iran and Faramarz Helali
of Luleå University of Technology in Sweden developed a
process for implementing practical ergonomics knowledge
transfer. Their motivation was to support the participatory
ergonomics process, using International Labor Organization
(ILO) ergonomic checkpoints, to support problem identifica-
tion and the implementation and development of feasible and
low-cost solutions. As presented in their paper, “Implementing
Practical Ergonomics Knowledge Transfer Using Ergonomic
Checkpoints to Support the Participatory Ergonomics Process
in an Industrially Developing Country,” this process empha-
sizes using two different tactics: the push tactic for intentional
learning and the pull tactic for voluntary learning.
This process was implemented in a two-year action research
study with the participation of all organizational levels in a
This month we highlight two articles from IISE
Transactions on Occupational Ergonomics and
Human Factors (Volume 10, No. 2). In the first,
a team led by Farzan Sasangohar found that
educating nurses on the impact of drowsy driving
results in a positive change in their beliefs to avoid
this dangerous behavior. In the second article,
the authors developed and applied a process for
implementing practical transfer of ergonomics
knowledge within a manufacturing company in an
industrially developing country.
Karim Zahed Alec Smith
Anthony McDonald Farzan Sasangohar
September 2022 | ISE Magazine 55
manufacturing company in an industrially developing coun-
try. Various technical sessions were held interactively between
an ergonomist facilitator and action groups using the ILO er-
gonomic checkpoints. Their goals were identifying and imple-
menting solutions to improve working conditions.
Their results show that the active participation of various
organizational levels, especially workers, increased participant
competence (both technical and social skills) in improving
working conditions, particularly low-cost and easy solutions,
as well as promoting a culture of participation, learning and
institutionalizing ergonomics principles in practice.
CONTACT: Faramarz Helali; faramarz.helali@gmail.com; Department of So-
cial Sciences, Technology and Arts, Humans and Technology, Luleå University
of Technology, 971-87 Luleå, Sweden
Yu Ding is the Mike and Sugar Barnes Professor of Industrial and
Systems Engineering at Texas A&M University and Associate Direc-
tor for Research Engagement at the Texas A&M Institute of Data Sci-
ence. He is editor-in-chief of IISE Transactions and a fellow of IISE.
Maury Nussbaum is HG Prillaman professor at Virginia Tech in the
Department of Industrial and Systems Engineering, editor-in-chief of
the IISE Transactions on Occupational Ergonomics and Hu-
man Factors, and a fellow of IISE.
Nosrat Abdollahpour Faramarz Helali
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LEGACY
IISE Transactions (link.iise.org/iisetransactions) is IISE’s flagship
research journal and is published monthly. It aims to foster exchange
among researchers and practitioners in the industrial engineering
community by publishing papers that are grounded in science and
mathematics and motivated by engineering applications.
IISE Transactions on Occupational Ergonomics and Human Factors
(link.iise.org/iisetransactions_ergonomics) is devoted to compiling and
disseminating knowledge on occupational ergonomics and human
factors theory, technology, application and practice across diverse
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