Advancing Public Health and Medical Preparedness with Operations Research –Paper 1
Q1. What is the RealOpt System and its objectives?
Realopt is a real time decision support system. This system combines OR modelling
techniques, innovative and large scale computational engines and advanced graphical drawing
tools. The objective of the system is to maximize the population that can be served while
minimizing the number of deaths and illnesses.
Q2. What are the benefits of RealOpt System?
The system has both Quantitative and Qualitative benefits:
Quantitative Benefits: Widespread adoption, Use in Planning and Actual Operations,
Preventing illnessi Reduction of labor requirements and Establishment of knowledge data
bank
Qualitative Benefits: Reduction in Planning Time, Reduction in waiting time and cycle time,
Providing Quality Assurance and Training, Improving mass disoensing capabilities and
efficiency
A Decision-Making Tool for a Regional Network of Clinical Laboratories – Paper 2
Q1) Optimization models are widely used and preferred models. There are lots of research
papers which optimization models are used in. This article is also a good example for
maximal covering problems. However, the important questions are why did the authors do
this research and what are the results of the study?
Answer:
The goals of the project are creating a new reference model to increase cooperation between
laboratories, planning a new procedure to better utilize RNCL’s laboratories and decreasing
total cost by reducing the number of outsourced tests. At the end of the study, costs fells from
8 million € in 2008 to 0,2 million € in 2009.
Q2) Some problems in logistics contain numerous nodes, and eventually many possible routes
while trying to find an optimal solution. This situation might be a drawback to find the
optimal solution. How is this problem handled in this article?
Answer:
In this article, in order to enhance logistics management, the model created with 47000
variables and approximately 36000 constraints. This is because there are so much possible
points for service centers and demand points. Since this is a huge model, they apply an
optimization engine. However, finding an exact solution to this RNCL planning problem is a
challenge despite the optimization engine, because the computation takes too much time. So,
they use a heuristic approach by making the engine work and stopping it after 1800 seconds
of computation. They found that the gap between the feasible solution after 1800 seconds and
the optimum solution at the end is just 10%. They think that 10% gap is bearable. So, it is
found that this heuristic gives credible feasible solution for this kind of planning problems.
Weekly Scheduling Models for Travelling Therapists- Paper 3
1) Why did they use heuristic in model 3?
It is almost impossible to solve the model without heuristic due to complexity of the model.
Therefore, they use heuristic in model 3 to find feasible solutions and also to decrease CPU
times.
2) Which model is cost efficient between Multiple Depot Vehicle Scheduling Problem and
Single Depot Vehicle Scheduling Problem? Why?
MDVSP is cost efficient because patients’ homes are spread over a great area. Therefore, if
we start physiotherapists from different depots instead of one single depot, transportation cost
and time decreases.
Dynamic Redistribution of Mitigation Resources During Influenza Pandemics- Paper 4
Question 1: Why is it thought that there will be no immunity in humans against the influenza
in the future?
Because of a continuous reassortment and mutation of the influenza virus, an ominous
expectation exists today that the next pandemic will be triggered by a highly pathogenic strain
to which there is little or no pre-existing immunity in humans [3-5].
Question2: What kind of limitations can we face on the model?
The impact of public education and the use of personal protective measures (e.g., face masks)
on transmission, cannot be measured effectively, that’s why there will be such limitations on
the model.
Question 3: What kind of improvements can be made on the model?
Future research efforts should focus on improving both model validity and its practical
usability
Incorporating recycling into post-disaster debris disposal – Paper 5
Two main questions involved in the article:
1) What are the differences between disaster debris cleanup and every day solid waste
disposal?
The authors offer the following ways that disaster debris collection and disposal differs
qualitatively and quantitatively from everyday solid waste collection and disposal:
1. Local municipalities are immediately overwhelmed and must quickly relate to many other,
often unfamiliar, organizations responding to the disaster that are not part of everyday solid
waste or routine debris collection activities. These organizations may include other federal,
state, and local government agencies, public utilities, contractors, and sub-contractors. In a
disaster, huge numbers of contractors and sub-contractors all converge at the disaster area e a
phenomenon that does not occur in routine solid waste and debris collection, which typically
involves only resources from the municipalities’ public works department or one, usually
long-term, solid waste contractor.
2. In large-scale disaster debris removal and disposal operations, municipalities lose
independence and freedom as federal, state, and other local municipalities’ requirements,
needs, and values become more important than individual autonomy. For example, disposal
operations are driven by FEMA (Federal Emergency Management Agency) reimbursement
requirements, which are implemented as part of a federal disaster declaration.
3. Because of extreme amounts of debris resulting from a disaster, municipalities are subject
to very different performance standards. In everyday solid waste disposal, the amount and
location of waste are either known or can be reasonably predicted for optimal allocation of
resources. Following a disaster, the volume and locations of debris are unknown and
estimates are often not accurate. In fact, the most widely used tool for estimating debris
volume provides estimates within a 30% margin of error. Volume and location information
tends to emerge as cleanup operations are carried out. These factors lead to three important
considerations. First, instead of offering a minimum level of curbside debris collection,
typically one day a month as in everyday solid waste collection, the objectives in disaster
debris operations focus on distributing maximum available resources equitably across the
affected area while simultaneously seeking to minimize time and cost of cleanup. Second,
because of the uncertainty surrounding demand, disaster coordinators route collection
vehicles to both primary and secondary TDSR (temporary disposal and storage reduction)
facilities in order to improve operational efficiency, reduce congestion, and apply appropriate
RSR technologies. In everyday solid waste collection, the need for secondary assignments
would be extremely rare. Third, existing landfill capacities are typically exceeded by more
than several years’ capacity or at least become significantly strained. Consequently, TDSR
facilities, which perform RSR (reduction, separation and recycling) activities, are needed to
handle enormous debris volumes, maximize FEMA reimbursement, and improve efficiency
and timeliness of disposal operations. As a result, decision makers are challenged to locate as
many TDSRs as necessary in, or at least close to, the affected region. In the case of everyday
solid waste collection, objectives generally include seeking to locate a minimum number of
landfills and transfer stations as far away from the collection area as possible
4. In disaster debris disposal operations, public and private organizations interact at a faster
and closer level, circumventing every day policies and practices. Because disaster generated
debris often results in mixtures that are uncommon, it creates complexities that make it
difficult to comply with landfill separation and disposal protocols followed under normal
conditions. As a result, standard operating procedures for disposal are often relaxed or
overlooked in lieu of cleaning up the area as fast as possible. In addition, policies for
contracting and bidding are also frequently bypassed in order to more quickly obtain needed
resources.
2) How would a facility location model be developed that incorporates FEMA’s new
recycling incentives and assists disaster management coordinators with locating
TDSR facilities?
The type of location problem that is of interest in the article is the Fixed-Charge Location
Problem (FCLP), which developed from the basic P-median model formulation. In the basic
formulation of the FCLP, a fixed cost is added to the original variable cost objective (usually
consisting of transportation costs) and the constraint requiring the number of facilities to be
located is removed from the general P-median model. Subsequently, the optimal number and
location of facilities is determined as the cost objective is minimized.
In general, the Fixed-Charge Facility Location model uses the objective of minimizing the
average (total) cost of locating facilities. Furthermore, the fixed-charge model and the Pmedian model that it was derived from are commonly used in situations where the goal is to
achieve overall efficiency of all facilities.
Disaster planners, for example, are interested in where to locate TDSR facilities so that the
total transportation costs for debris cleanup teams to travel from debris locations to TDSRs is
minimized.
In addition to travel costs, planners are also interested in how many, what type, and where to
locate TDSRs so that the fixed opening and closing costs, RSR costs, and final disposal costs
are minimized.
Finally, in response to FEMA’s recent policy change, disaster planners should also consider
the effect that recycling operations have upon the decision of what type of TDSRs to activate
and where they should be located. All of these factors are important in negotiating favorable
contractor agreements and in helping to minimize the social, economic, and political effects
across the affected region. With these considerations, the general Fixed-Charge Facility
Location Model is modified to formulate a model for the TDSR-DLP. (Please see the article
for the mathematical model and further discussion)
Improving Access to Health Facilities in Nouna District – Paper 6
1-) Why do we use the transformation about E and Lp in our model?
If the edges both take place on E and Lp , it means that these existing edges have the
possibility to be improved. This situation makes our model more complicated. In order to
separate them, the distance between I and j node is separated into two equal pieces which
named diu and duj. diuE , dujE and dijLP are separated each other because of this transformation.
By this way, our model is made clearer in order to solve the model.
2-) What is the main difference of the model that we saw in class (the facility location
problem) and FLND (facility location-network design) problem?
The model that we saw in the class only considers the Euclidean distances between the nodes.
However, the FLND considers the real roads distances and aims designing a network by using
an existing road or upgrading road besides covering as much as people as we can.
An Auction Based Frame-Work for Resource – Paper 7
1) What does "Ease-of-logistics parameter" mean ?
Infrastructural and geographical convenience of the supplier and the disaster location. In
addition, the concept considers the suppliers’ experience at the disaster location and in
similar disaster types.
2) What are the 3 phases in the paper of "An auction-based framework for resource allocation
in disaster relief"? (Also, please state that who does conduct the phases -auctioner or bidder-)
- Announcement construction (by auctioner)
- Bid construction
(by bidder)
- Bid evaluation
(by auctioner)
Ornge – Paper 8
1- We know that determining how to schedule and route available aircraft to handle
these requests at minimal cost is complex. Why?
Answer;
Because of 4 side constraints that are:




Aircraft can handle up to approximately four requests within a duty shift.
Some aircraft can carry up to two patients while others can carry only one.
Some patients cannot be transported with another patient because of infections.
Requests can be handled in any order subject to certain time restriction
2- What are the main limitations for Ornge?
Answer;
-
Weather conditions
Effect of unscheduled urgent/emergent calls
Difference between final cost and cost that modelled in the optimization tool.
Obesity – Paper 9
Q1:
What is the relation between economy and obesity?
It is a precondition or obesity; because in order to a population to develop obesity,
there should be sufficient wealth. Also relation between gross domestic product and
body mass index is linear up to $50000. It shows that as long a economic wealth
increase but up to a point, body mass index increases. It means obesity is increasing.
But there is an anti example for this situation which is Pacific Islands. Their economic
prosperity is low but obesity is high in those islands. Actually they are world’s most
obese countries. It shows that there are other elements that determines obesity
different than economy.
Also economic transition effects obesity too because
countries which has low economic prosperity starts to increase their economic
prosperities and it increases obesity level. Children which are fed with unhealthy
foods in low economic prosperity becomes adults which can eat more food and it
increases obesity with different diseases which caused by unhealthy background.
Q2:
Is there a role of gender to be affected from obesity?
Obesity is risky especially for women in most of the countries. Although it changes with the
cultural beliefs of a country such as in China small sizes have positive attribute instead of the
large sizes in Tongan, researches show that obesity is a prevalent risk factor for especially
adult women around the world.
Disaster Relief Routing - Paper 10
Question 1
Q: What are the objectives of egalitarian and utilitarian models?
A: Egalitarian: Maximizing equality of a measure such as delivery quantity or time.
Utilitarian: Maximizing the amount of demand satisfied without requiring equality in
distribution of goods.
Question 2
Q: What are the uncertainities in vehicle routing problems? List 4 of them.
A: Demand, Supply, Accessibility of roads in post disaster period, Safety of drivers and the
goods that are sent.