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10/1/2019
Aeren Foundation
INDIAN SCHOOL OF BUSINESS
MANAGEMENT AND ADMINISTRATION
AN ISO 9001:2015 CERTIFIED
INTERNATIONAL B-SCHOOL
Name :
Farid Ahmad Noory
Marks : 80
Course :Masters
in Business Administration (MBA 4 Sem)
Subject : Quantitative
Methods
Case Studies
Linear Programming
(20 Marks)
Lexicographic Goal
Programming is used to solve a series of Linear Programming Model. This
programming is used wen . a goal has to be attained on•priority basis. Revenue
budgeting is being used to decide budget instead of a specific system in
budget. Nevertheless, revenue budget lays emphasis on the rising limitation of
revenue while estimating budget. The decision makers are limited due to the
rising power of capital and also the awareness of imminent restraints and fear
of capital resources. The goal is to raise the salary and allowance of the
workers,to cut down the operating cost, to raise the revenue expenses, to raise
the capital generated internally, and the cut down the overall budget. Some of
the problems are: insufficient allocation of funds and income, and• absence of
importance of order. The insufficient allotment occurred as the quantitative
allotment models were not used with power. . It is seen that the allotment of
capital were not being used in the right" way as a result the capital allotted
to the labs is drawn •in the maintenance of hostel. Various other changes also
happen. In fact, the funds allotted to the tertiary organizations are more
often not managed properly. The University of Owerri suffered and the progress
of the institution came down. There is absence of active teams for monitoring
budget, and so the budget can function in any manner. If the active teams to
monitor budget were present, the problem of mismanagement and the wrong use of
it would come down. Sundaram (1978) and Lee (1972) agreed that the various
features of target programming are, that it allows ordinal solution. According
to Igniio (1978), this tactic called Goal Programming, frequently symbolizes
considerable progress in the modeling and evaluation of the multi objective
problems. This shows that this area lets the systematic evaluation of a number
of multi objective problems which could include linear or non linear operations
in the incessant or separate variables. This is most successful in the research
area. The goal programming developed due to Charnes and Cooper, who suggested
that the model and method for dealing with some linear programming problems
where the contradictory 'goals of management' involed as limitations. Goal
programming method has been used for a number of programs. Goal programming
technique has solved the following problems: planning production in a ship
repairing company, smoothing production in 'just in time' production
atmosphere. The problem occurs when the model does not show the real inclination
of the decision maker. Non-inferior solution in some cases many not be
essentially better than the lesser solution mainly in the case of natural
resource problem.
Answer the following
question.
Q1. What are the
problems while estimating the budget?
(Hint: insufficient
allocation of funds and income, and absence of importance of order, The
insufficient allotment occurred as the quantitative allotment models were not
used with power)
Answer : There are a
number of serious problems associated with budgeting, which include
gamesmanship, excessive time required to create budgets, and budgeting
inaccuracy. In more detail, the problems with budgeting include:
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Case Study
Finoplastika Industries Ltd, Nigeria
(20Marks)
Time series analysis
has two important aims:
1) recognizing the
quality of the phenomenon shown by the series studies, and
2) Both the aims need
the plan of the viewed time series data is recognized and somewhat official explained:
A time series is said to be a 'collection of observations made in sequence with
time'.
For example: recording
level of daily rainfall, periodical total domestic product of US, and monthly
strength of the. workers in Marine Corps for specific rank and MOS. The
evaluation of time series gives instruments for picking a symbolic model and
delivering forecasts. There are two sorts of times series data:
• Continuous: in this
the data consists of study at every moment, f example, seismic movement
recorded on a seismogram.
• Discrete: the data
contains recordings taken at different periods ,like, statistics of each month
crime. Until the data is absolutely haphazard, studies in time series are usual
related to each and the following studies could be partly ascertain by the last
values. For instance, the reason pertaining to the meteorology which have an
effect on the temperature for any given day tend to have some affect on t next
day's climate. Hence, the observations of the past temperature are helpful for
predicting temperatures for t following days.
• A time series can be
deterministic if there are no haphazard or feasible features but goes in a set
a foreseeable manner. The data gathered during the classical physics experiment
like showing Newton's Law of Motion, one example of a deterministic time
series. The stochastic type of series is more appropriate to the economist
function. Stochastic variables contain undefined or arbitrary viewpoint. Though
the worth of each study cannot precisely foreseen, calculating the various
observations could follow the expected method. These methods can explained
through the statistical models. According to these models, studies differ
erratically on the underlying mea value which is the role of time. Time series
data can be put in the following categories: one or more performance facto
trend, seasonality, cyclical function and random sound. Various kinds of time
series predicting models give forecas through extrapolating the previous
performance of the values of a specified \'l!riable of interest. Consecutive
study econometric times series are generally not free and forecast can be made
on the basis of last observations. Althou precise predictions can be made with
deterministic time series, predictions of stochastic time series are restricted
'conditional statements regarding the future on the basis of particular
hypothesis.' Armstrong (2001) says, "The bas Assumption is that the
variable ui!! continue in the future as it has behaved in the past. "
Particularly, the time seri predictions are suitable for stochastic type of
data in which the fundamental root cause of variation like, trend, cyclic
performance, seasonality, and uneven variations, do not change radically m
time. Therefore, modeling is considered be more suitable temporarily instead of
permanent predictions.
Answer the following
question.
Q1. Write briefly on
time-series analysis.
(Hint: recognizing the quality of the
phenomenon shown by the series of studies, and, both the aims need the plan of
the viewed time series data is recognized and somewhat officially explained)
Answer : Finoplastika
manufacturing industry limited is a
company producing plastics in
different shapes and
sizes. They produce both
injection and extrusion
plastics. Injection plastics are domestic plastics (e.g. bucket,
cup, spoon, etc.), plastic
furniture (e.g. chairs, tables, etc) and industrial plastics (e.g. Toilet
cover, laptop cover, television cover, etc. Over the years, the company has made substantial progress. However there is no formalized way of determining what quantity of different products to
be produced over any given period
of time. This leads to inconsistencies in planning and production. To
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Case study
A Network Rail
(20 Marks)
The railways play an
important role in the economy and infrastructure of Britain. Not very many
people travelled back jn the 1920 as compared to present time, in spite of 50%
reduction in raif routes as compared to the 1960s. Rail is also used for
transporting goods around Britain. Rail proves to be• more eco-friendly and
safest means of transportation as compa;ed to other vehicles so, not
surprisingly, the number of people commuting have gone 40% more since the past
ten years. By 2034, this figure can go up. The work of network rail has to look
after the tracks, bridges and tunnels which comprises of the British rail network.
The railway infrastructure is made up of signals and level crossings. It has to
look after the 20,000 mile long track and 40,000 bridges and tunnels. Britain's
18 main rail stations, from Edinburg Waverley to London King's Cross, are
looked after by the Britain rail system. Ten years ago, when the network rail
took up these responsibilities, • it had to face some challenges. The rail
neork was facing some problems. Trains were running late, the costs were too
high and there was shortage of assets in both the people and machinery. Due to
these issues, people had less confidence in the rail network. Ever since then,
rail network has aimed at sustaining operations to reduce the expenses. There
has been 28% reduction in expenses mainly because of conomy of scale. New
tracks and machinery have been bought, and there has been 90% rise in the rail
punctuality. Huge projects have been given on time an towards th budget, as a
result the confidence of the people has improved. Rail network has moved from
'find and fix' to 'predict and prevent' policy. This has proved to be more cost
effective and competent and enabled in avoiding delay or obstruction for the
people in their travel. The rail network invested approx. 12 billion pounds
between 2009 and 2014, towards the rail network. Britain has the fastest
developing network in whole of Europe. By investing in people, the rail network
is investing in the future to. .B ritain has the largest working personnel of
35,000 workers. It has people working in various positions, like, engineers for
maintenance and signaling to project managers. Each area offers an opportunity
to work. They also consist oi HR (human resources), IT (information
technology), and finance and customer service. Network Rail needs to employ and
keep capable engineers in order to get the work done. Presently, its engineers
are doing some oi the most stimulating projects in Europe. The projects include
HS2, which is the new super spted rail link between the north and south
Britain, and the project of London Crossrail. Some oi the biggest and busiest
rail stations are being upgraded, like, London King's Cross and Birmingham New
Street. The main focus of the HR of Network Rail is to recruit various
personnel. This not only deepens the culture of business but it also makes sure
that it can reach every talent. It offers training for every applicant, whether
he is a school drop-out or a graduate, whether male or female, a continued flow
of appropriate talent is ensured to keep its long term project going. The company
abo gives many opportunities to its workers to receive recognized
qualifications, such as an exclusive programme in post graduation, sponsoring
the Master's Degree in project management and trainee.
Answer the following
question.
Q1. What were the initial
problems that Network Rail of Britain face?
(Hint: It has to look
after the 20,000 mile long track and 40,000 bridges and tunnels. Trains were
running late, the costs were too high and there was shortage of assets in both
the people and machinery) Q2. What is the new super speed rail link between the
north and south Britain called? (Hint: HS2)
Answer : What is
Network Rail?
Network Rail (NR) was
set up in 2002 to replace Railtrack as the body responsible for Britain's rail
network. It holds a monopoly over Britain's rail infrastructure, a major
national asset, and as such is rigorously monitored to ensure accountability to
the public interest. Its network operating licence was originally issued to
Railtrack on March 31st 1994.
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CASE STUDY
(20 Marks)
The bulbs manufactured
by a company gave a mean life of 3000 hours with standard deviation of 400
hours. If a bulb selected at random, what is the probability it will have a
mean life less than 2000 hours?
Answer the following question.
Q1. Calculate the probability.
Ans.
Q2. In what situation does one need probability theory?
Ans. Probability
theory is applied to situations where uncertainty exists. These situations
include
Q3. Define the concept of sample space, sample points and events in
context of probability theory.
Ans. sample spaceÃ
Definition: The
sample space of an experiment is the set of all possible outcomes of that
experiment.
The
sample space of Experiment 1 is: {head,
tail}
Q4. What is the difference between objective and subjective
probability?
Ans.
Objective probability is where I know that if I toss a fair coin enough
times, it’ll turn up heads 50% of the time. Subjective probability is where I think there’s a 10% chance
it’ll rain tomorrow, and I don’t care to repeat the event. The former is an
informed statement about a system. The latter is our
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