Parcel Service (UPS) started in 1907 as an...
Parcel Service (UPS) started in 1907 as an American messenger service firm.
Over the years, the company grew to where their services shifted from just
private couriers and delivery to including retail package delivery in their
services. By 1929, the company had adopted offering limited air delivery
services for clients who needed their services between some west coast cities
of the U.S. The company had developed to the extent of offering two-day
delivery services in the main cities from coast to coast by mid-1950s. The
company received a boost when they were allowed to provide their delivery
services to all the 50 states by the federal authority. The company ever since
has grown to the extent where they have expanded even to the rest of the world.
The company became more complicated with more responsibilities as the schedules
were tight. The services were done in this manner for the purpose of being more
competitive in the delivery industry against their rival companies like FedEx
Corporation. The organization, therefore, resolved in finding solutions to
optimize their services in matters of spending their delivery by optimizing the
air network Through the use of an application developed within the organization
known as the Volume, Location, and Aircraft Network Optimizer (VOLCANO). This
report will consider the problem the group was trying to solve, the results of
the solution, the implementation process and the shortcomings of the solutions
problem and its context
UPS airline delivery service operates in three different categories which
include same day, next-day, and second-day deliveries. The company operates its
network of all-points hub to ensure that the next-day deliveries are run
smoothly. Additionally, the company has set strict deadlines for its customers
to ensure they allow time for sorting the deliveries according to the
destination before departure. Any late goods are to be delivered in the
following scheduled pick up which is in the next day, and same day. The problem
in this situation was on the next-day deliveries. The program runs under strict
deadlines where the clients have to drop off the goods they need to be
delivered between 6.00 pm and 8.00 pm. The company must deliver the goods to
the destination by 10.30 am on the following business day which requires the
organization to run its airports, aircraft, and hubs efficiently. The company
has overflowing clientele where an average of more than 1 million packages is
delivered in a single night from various branches of the organization. At every
stop, packages are sorted regarding those being packaged to leave the hub for
an outbound aircraft to those being unloaded to be loaded into trucks for
deliveries at the destinations.
for the plane routes, therefore, required lots of time and efforts as it
involved numerous aspects. Some of the aspects include; sufficient speed to
meet the deadline, restrictions on landing locations, maximum flying range and
the cargo capacity of the aircraft. Manual planning presented a problem which
was routes reversal where an aircraft could only travel one way which was the
path to one airport or hub and back which would not utilize the aircraft to the
maximum. The planning of this sort took up a large number of workforces from
the planning and analyst sections of the organization. For example, three
separate groups of planners worked in different next-day issues where they were
tasked with identifying the most efficient route for the aircraft and package
movements to ensure cost efficiency and timely deliveries. It would take the
organization up to nine months to complete a single plan. The nine months
period did not include analyzing the project and learning its workability. And
with the broad range of data due to the dynamics of the organization, the
planning process was becoming harder by the day. Planners and the analysts in
the firm suffered the most as the task was on their hands. Finding solutions to
all these problems was important for the company as it needed to maintain its
timely deliveries, save on the cost by utilizing the aircraft’s capacity to the
fullest and finding better routes to be able to save on the cost.
organization focused the project on the next-day air system as planning with
this category would allow the people involved to focus on a broad range of
scenarios as the next-day network is more complex than the other two. By using
the next day, it would also help create viable plans and to be able to generate
an optimal plan for the next-day network. The project was based on optimization
approach. The people involved used three methods to test and solve the problem.
It was aimed at developing optimization methods. Through the optimization, the
company would be able to save on the cost through determining the package flow
and movements of the aircraft hence minimizing ownership.
of the greatest challenges with the project was actualizing the theoretical
concepts by presenting them to planners who were the ones tasked with approving
them which is something that had never been done before. The team working on
the project also faced problems in the process of actualizing it where the
system itself presented a challenge in the network design components. The
system itself ha to determine and match various aspects like minimum cost set
for the route, package flows, speed, loading capacity and more. In other words,
it was actualizing the system to optimize the full operation as it was supposed
to function. The air design problem includes two decision variables which were
integer-valued decision variables and would represent aircraft-routing
decisions and continuous decisions variables which would represent package
flow. Constrains presented the issue of tractability. The issue and much more
showed the ineffectiveness of conventional means of trying to solve the network
design problems. The team involved in the project abandoned resolving the
problem with conventional ways and instead they adopted an interface design
formulation whose linear programming relaxation was stronger. The group
combined packages and aircraft routes to be a single integer-valued decision
variable rather than using them separate as the previous proposition dictated.
All this was in pursuit of optimal values of the cost of operation of the
than technical challenges, the team faced organizational obstacles like
resistance from the senior managers in the organization and the planning department.
The management required the research team to justify proceeding with the
project the planning group, on the other hand, saw the technological program as
a threat as they had relied on their knowledge and skills for a very long time
in the planning of the organization. The team also faced the challenge of
receiving research funds. Although they were granted, the finances took very
long to be processed. The team was, however, able to gain trust from the
management through the monitoring, going through the documentations and seeing
the progress made by the team. Through the participation of one planner, the
team was able to gain favor from the rest of the executives in the firm as the
single one on their side advocated for the changes they were a helped convince
the rest on the workability of the project.
first results showed that conventional network design formulation needed more
effort as compared to the combined variable formulation to get to the optimal
value solution. The result was a seven percentage reduction on the operation
cost. According to the organization’s saving, this would project to lots of
millions for the company in just one year. Most of the savings come in the
total number of aircraft in the operation as they would reduce and also on the
ownership cost. As compared to the nine months period required by the planners
to plan and additional time to analyze for the next-day air network, this
technology would do all this planning and analysis in just two hours of
running. The planners, however, are unable to adopt the VOLCANO fully but only
use it to identify areas that need to be changed in their existing network
plans. The use of the system is limited which means that the organization uses
it as a tool to help in making organizational decisions, but they will soon
realize the economic potential of the system.
program was implemented in 2000 and continued to be refined where it continues
to cover more than just the next-day air network but includes the international
delivery, three-day select, and second-day air. Since its implementation,
VOLCANO has acted as more than just an optimization model. The system handles a
variety of information which include; time windows of customer services,
operating characteristics for aircraft, those of hubs and airports and volumes
that move through the air network. The model has achieved in creating a precise
timing that is required in scheduling the operations. The VOLCANO was
integrated with the existing UPS databases and manipulated the data to be
usable. An additional pre and post processing modules were built which was
helpful in generating useful output for planners. A commercial off-the-shelf integer and linear
programming solver were used for the core analytical engine. The programming
solver used was the ILOG CPLEX Callable Library. The C++ language was used to
generate columns and structures for the integer program. The whole program runs
on a Hewlett Packard N4000 machine where the HPUX 11 is the operating system.
has impacted on the organization in different ways. One of the impacts is the
quantifiable cost saving. The impact is both short term and long term for the
firm. The planners on the organization have used the VOLCANO since 2000 to make
changes to the existing plans. The cost that has been reduced is the operating,
ownership and even leasing cost. The operating expenses are crew and fuel;
ownership is the cost of buying and maintaining the aircraft, and the leasing
cost is one incurred in high season when the organization has to obtain
additional aircraft through rental to increase their capacity. An example of a
change implemented by the help of the VOLCANO is the shifting of two planes
from the network to the poll spare aircraft in 2002 which reduced the cost of
operation. The system has enabled to firm to lessen the number of aircraft by
matching demand to the available capacity. The changes have helped reduce the
cost with as much as $87 million, and it is estimated to save as much as $189
million in the coming decade.
VOLCANO just like any other technological advancement will render some
individuals jobless. For example, the workforce that used to operate an
aircraft that has stopped working will be forced to look for another job. The
situation is also similar for the planners where a huge number of them will be
obliged to go home with no job since the system has taken lots of work from
their hands. The organization has become dependent on the system to help solve
problems and is used as a consultant, neglecting knowledgeable people,
therefore, rendering them jobless yet with the required skills.
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