The document provides an introduction to operations research (OR), including its origins in solving military problems during World War II, definitions, characteristics, methodology, application areas, and limitations. OR emerged as a field to help allocate scarce resources effectively for military operations. It uses scientific and mathematical modeling approaches to help executives make rational decisions. Some key points made in the document include: - OR is interdisciplinary and system-focused, drawing on techniques from multiple fields to analyze complex systems. - The OR methodology typically involves observing the problem environment, defining the problem, developing a mathematical model, inputting appropriate data, testing solutions, and implementing recommendations. - OR is applied across various domains including defense, industry, transportation,

1. IEP 107:
Operations Research 1

2. Introduction to
Operations
Research

3. Origin and Development of OR
> Operations Research has generally been attributed to the military
services early in World War II.
> There was an urgent need to allocate scarce resources to the various
military operations and to the activities within each operation in an
effective manner.
How?
 British military executives called upon a team of scientists to apply scientific
approach
 Study the strategic and tactical problems related to air and land defense of the
country.
 Develop effective methods to win the “Air Battle of Britain” then followed by
managing convoy and submarine operations that led them to win with
different battles

4. Origin and Development of OR
> It is said that Simplex Method is the first technique in the field
for solving linear-programming problem; developed by American
mathematician George Dantzig in 1947

5. What is Operations Research?
As the name implies, operations research involves "research on
operations". This says something about both the approach and the
area of application.
To define OR, we need to use the formula (method +
application). Here are some of definition of OR:
1. OR is the art of winning wars without actually fighting. (Aurther
Clarke)
2. OR is an art of giving bad answers to problems where otherwise
worse answers are given: (T.L. Saaty 1958)
3. OR is applied decision theory. It uses any scientific, mathematical or
logical means to attempt to cope with the problems that confront the
executive when he tries to achieve a thorough-going rationality in
dealing with the decision problems.
(D. W. Millar and M.W. Starr)

6. What is Operations Research?
Operations Research is a branch of mathematics used to
provide a scientific base for management to take timely and effective
decisions. It possibly avoids the dangers arising from
decisions based on guesswork.
The concept of management has basically two characteristics:
1. Multidimensional: Because managerial problems and their probable
solutions have repercussions in several fields such as human,
economic, social and political fields.
2. Dynamic: A manager will never remain static while prevailing in the
business.

7. Characteristics of Operations Research
The problems an operations research analyst faces are
heterogeneous in nature, involving the number of variables and
constraints, which are beyond the analytical ability of one person. So, a
number of people from various disciplines are required to understand the
problem.
It is an interdisciplinary team approach:
It helps in increasing the creative ability of the decision makers:
A manager, without the knowledge of these techniques, just takes
decisions by guessing or by trial and error method, which can give
troublesome result. Hence, a manager who uses Operations
Research techniques will have a better creative ability than a manager
who does not use these techniques.

8. Characteristics of Operations Research
When dealing with Operations Research problems, the system
should be treated as a whole so that the interrelationship between
sub-systems and the effect of the problem on the entire system are
kept in mind. Hence, Operations Research is
a systems approach.
It is a systems approach:

9. Characteristics of Operations Research
 OR approaches problem solving and decision making from the total system
perspective.
 OR is not only necessarily uses interdisciplinary teams, but it is also
interdisciplinary; it draws on techniques from sciences like biology, physics,
chemistry, mathematics and economics and applies the appropriate techniques
from each field to the system being studied.
 OR does not experiment with the system itself but constructs a model of the
system for conducting experiments.
 Model building and mathematical manipulation provide the methodology that has
perhaps been the key contribution to OR.
 The primary focus is on decision-making.
 Computers are used extensively.
The additional characteristics of operations research can be listed as
follows:

10. Operations Research Approach and
Methodology
Operations research is a logical and systematic approach to
provide a rational basis for decision-making. The phase and
processes of OR study must also be quite logical and systematic.
There are six important steps in OR study, but it is not necessary that
in all the studies each and every step is invariably present.
Step 1: Observe the Problem Environment
The activities that constitute this step are visits, conferences,
observations, research and so on. With the help of such activities, the OR
scientist gets sufficient information and support to proceed and is better
prepared to formulate the problem.

11. Operations Research Approach and
Methodology
Step 2: Analyze and Define the Problem
In this step not only the problem is defined, but also uses,
objectives and limitations of the study are stressed in the light of the
problem. The end result of this step is a clear grasp of need for a solution
and understanding its nature.
Step 3: Develop a Model
Operations research models are basically mathematical models
representing systems, processes or environment in the form of equations,
relationships or formulae. The activities in this step include defining
interrelationships among variables, formulating equations, using known OR
models or searching suitable alternate models.

12. Operations Research Approach and
Methodology
Step 4: Select an Appropriate Data Input
Garbage in and garbage out is a famous saying. No model will work
appropriately if data input is not appropriate. Hence, tapping the right kind of
data is a vital step in OR process. Important activities in this step are analyzing
internal-external data and facts, collecting opinions using computer data
banks. The purpose of this step is to have a sufficient input to operate and test
the model.
Step 5: Provide a Solution and Test Reasonableness
First, the solution is used to test the model and to find limitations, if
any. If the solution is not reasonable or if the model is not behaving properly,
updating and modification of the model is considered at this stage. The end
result of this step is a solution that is desirable and supports the current
organizational objective.

13. Operations Research Approach and
Methodology
Step 6: Implement the Solution
Implementing the solution is also identifying the gap between one
who provides a solution and one who wishes to use it should be
eliminated. To achieve this, OR scientist as well as management should
play a positive role. A properly implemented solution obtained through OR
techniques results in improved working and wins the management
support.

14. Operations Research Application Areas
OR has got wide scope. In general we can say that wherever there is
a problem, there is OR for help. In addition to the military, operations
research is widely used in many organizations including business and
industry.
1. In defense
OR helps the military executives and managers to select the best
strategy (courses of action) to win the battle. Thus, OR has got great scope
in defense.

15. Operations Research Application Areas
2. In industry
Seeing the success of OR in the military, industry became interested
in this new field. As companies expanded, it became less and less possible
for one man to manage them, therefore the job of one man was divided
into parts and assigned to others.
a. Production Department- To minimize the cost of production. OR is useful
to Production Specialist in (a) designing and selecting sites, (b) scheduling
and sequencing the production run by proper allocation of machines and
(c) calculating the optimum product mix.

16. Operations Research Application Areas
2. In industry
b. Marketing Department- To maximize the amount sold and to minimize
the cost of sales. OR is useful to the Marketing Managers in (a)
determining, when to buy, how often to buy and what to buy to minimize
the total costs, (b) calculating the minimum sale price per unit and (c)
knowing the customer's choice relating to color, packing and size etc., for
various products.
c. Financial Department- To minimize the capital required to maintain any
level of business. OR is useful to Financial Controller in (a) finding out the
long term capital requirements (b) finding out a profit plan for the
company and (c) determining the optimum replacement policies.

17. Operations Research Application Areas
3. L.I.C
OR techniques are also applicable to enable L.I.C. officers to decide
the premium rates of various policies for the best interest of the
corporation.
4. In Agriculture
With the increase of population and consequent shortage of food,
there is a need to increase agriculture output for a country. But there are
many problems faced by the agriculture departments of a country e.g., (i)
climatic conditions, (ii) problem of optimal distribution of water from the
resources, etc. Thus, there is a need of best policy under the given
restrictions. OR techniques may be fruitful to determine the best policies.

18. Operations Research Application Areas
5. Planning
Careful planning plays an important role for the economic
development of a country. OR techniques may be fruitful for such
planning.

19. Future of Operations Research
There also are some important trends under way now that suggest
that this impact should further increase in the future. We briefly describe
some of these trends:
• The rise of analytics
Analytics involves combining OR with some related techniques that
largely involve dealing more effectively with the sometimes massive
amounts of data that now are available to organizations. These related
techniques further expand the toolkit of OR analysts while successful
applications of analytics further elevate the recognition of the power of
operations research.

20. Future of Operations Research
• Increasing use of artificial intelligence and machine learning
It has long been recognized that artificial intelligence (simulated
intelligence in machines where these machines are programmed to “think”
like a human and mimic the way a person acts) and machine learning (a
method of data analysis that automates analytical model building by using
statistical techniques to give computer systems the ability to “learn”
without being explicitly programmed) will become very important tools of
operations research. It now is becoming clear that this trend already is well
under way.

21. Future of Operations Research
• Many applications to transportation logistics
OR is ideally suited for dealing with the technological and
economic forces behind the unprecedented wave of innovation and
investment we are beginning to see in transportation.
• Using network optimization models for public good:
For example, some studies now focus on unconventional supply
chains of blood, medical nuclear materials, food, and disaster relief while
avoiding the perishability of the products.

22. Future of Operations Research
• Numerous OR applications to healthcare
A few examples of the numerous applications include surgery
planning and scheduling, optimizing chemo radiotherapy for cancer
treatment, patient flow control, optimization of support functions, medical
decision making, and public healthcare policy.
• The rise of behavioral queueing theory
An important very recent development in queueing theory is the
introduction of behavioral queueing theory to consider the impact of behavioral
factors on the performance of queueing systems. Rather than making simplifying
assumptions that human servers and customers always will operate like robots
that are programmed to satisfy these assumptions, the goal is to use the actual
typical behavior of human servers and customers to obtain more accurate
measures of performance.

23. Limitations of Operations Research
• Magnitude of computation
In the modern society, these factors are numerous and expressing them in
quantity and establishing relationship among these, requires huge calculations. All
these calculations cannot be handled manually and require electronic computers
which bear very heavy cost. Thus the use of OR is limited only to very large
organizations.
• Non-quantifiable factors
Operations research provides solution only when all elements
related to a problem can be quantified. Operations research does not take
into account qualitative factors or emotional factors which may be quite
important.

24. Limitations of Operations Research
• Distance between a manager and operations researcher
Thus, there is a gap between the two. Management itself may offer
a lot of resistance due to conventional thinking.

25. Limitations of Operations Research
• Money and time costs
When the basic data is subjected to frequent changes,
incorporating them into the OR models is a costly affair. Moreover, a fairly
good solution at present may be more desirable than a perfect OR solution
available after some time.
• Implementation
Implementation of decisions is a delicate task. It must take into
account the complexities of human relations and behavior. Sometimes,
resistance is offered only due to psychological factors.

26. END.

27. Scenario Analysis
1. Case study: Make Versus Buy Case
Objective: To deliver timely
2. Identify activities in each OR methodology
Step 1: Observe the Problem Environment (What?)
Step 2: Analyze and Define the Problem (What?)
Step 3: Develop a model (How?)
>> Since we’re in the introduction of OR, how the OM/ OR
will develop a model.
Step 4: Select an Appropriate Data Input
(No need to answer the ff steps)
Step 5: Provide a Solution and Test Reasonableness
Step 6: Implement the Solution
** Answers will be uploaded on pinnacle in PDF form.
>> Make Decision if to make or to buy