Introduction to OR

1. SOUMENDRA ROY

2.  Decision is important in everyday life
 Business decisions are becoming more and more
complex
 In business, decision makers not only faced with a
large number of interacting variables but has to
take into account the actions of the competitors
 Business decisions cannot be taken only on the
basis of intuitions
 Some formal system is required is needed to
determine an effective course of action
 Understanding of the possible use of scientific
approach to decision making is of great
importance to the business students

3. PROBLEM
OPERATIONS
RESEARCH
JUDGEMENT
DECISION
EXPERIENCE
DATA

4.  Decision problems of modern management are so
complex that only a systematic and scientifically
based analysis can yield realistic solutions
 Availability of different types of quantitative
models for solving these complex managerial
problems
 Availability of high-speed computers has made it
possible both in terms of time and cost to apply
quantitative models to all real-life problems in all
types of organizations such as business, industry,
military, government, health and so on
 Operations Research is not decision making

5.  Evolved during the WW II, to allocate the scarce
military resources in an effective manner
 After the WW II, the apparent success of the
military team attracted the industry, which was
seeking solutions to problems caused by
increasing complexity and specialization in the
organization
 OR originated in India during the last phase of the
WW II
 OR in India started in 1949 with the opening of a
unit at the Regional Research Laboratory,
Hyderabad for using OR in planning and organizing
research

6.  OR got its formal recognition in the country with
the formation of O.R. Society of India in 1957
 Several efforts to promote OR was made
 Result in encouraging the formation of a number of
O.R. groups in organizations such as Planning
Commission, Railways, PSUs, e.g., BHEL, SAIL,
ONGC, etc.
 O.R. education was formally initiated in India with
the formation of IIM at Ahmedabad and Kolkata
 Industries, government and other agencies are
gradually becoming conscious of the role of
Operations Research in decision making

7.  INDUSTRY
 Forecasting of market requirements
 Minimization of transportation cost
 Optimal distribution patterns
 Optimal replacement and maintenance of parts and
equipments
 Materials management and purchasing problems
 Cost-effectiveness studies
 Reliability of systems and manufacturing plants,
production, etc

8.  TRANSPORTATION
 Performance of drivers
 Analysis of freight movement
 Marshalling yard operations
 Cost-effectiveness analysis of additions crews
 BANKING AND FINANCE
 Credit planning
 Location of branches
 Cash Management
 Project Appraisal
 Corporate Planning

9.  AGRICULTURE
 Improvement of crops
 Distribution of seeds
 Optimization of agricultural land and facilities
 DEFENCE
 Logistics
 Cost-effectiveness studies regarding choice of gun
systems, rockets, missiles, etc.
 War-gaming and simulation to devise optimal
tactical plans as well to provide training to
commanders

10.  ENERGY
 Manage the refinery operations of Oil companies
 Electric and hydro-electric companies use OR techniques to
determine how to efficiently produce power as well as trade
power among their partners
 HEALTH-CARE
 Quality assurance
 Design of medical informatics
 Emergency room scheduling
 Resource modeling diagnosis
 Logistics
 Revenue Management
 Manufacturing and Development of drugs
 Management of drug portfolios representing the assortment
of different drugs maintained by companies

11. “Operational Research is the application of the
methods of science to complex problems arising in
the direction and management of large systems of
men, machines, materials and money in industry,
business, government and defence. The distinctive
approach is to develop a scientific model of the
system, incorporating measurements of factors
such as chance and risk, with which to predict and
compare the outcomes of alternative decision
strategies and controls. The purpose is to help
management, determine its policy and actions
scientifically.” - O.R. Society of U.K

12.  O.R. approaches problem-solving and decision-making
from the total system’s perspective. O.R. does not
experiment with the system itself but constructs a
model of the system upon which to conduct
experiments
 O.R. does not necessarily using interdisciplinary teams,
but it is interdisciplinary; it draws on techniques from
sciences such as biology, physics, chemistry,
mathematics, and economics and applies the
appropriate techniques from each field to the system
being studied
 Model building and mathematical manipulation provide
the methodology which has been the key contribution
of O.R.

13.  O.R. is for operations economy
 O.R. emphasizes on the overall approach to the
system, i.e., all the aspects of the problem under
consideration
 O.R. tries to optimize the total output by
maximizing the profit and minimizing the loss (or
cost)
 The primary focus is on decision making and
computers are used extensively

14.  JUDGEMENT PHASE
o Determination of the operation
o Identification of the real-life problem
o Establishment of the objectives and values related
to the operation
o Determination of the suitable measures of
effectiveness
o Formulation of the problems relative to the
objectives
o Building of an appropriate model of the problem
abstracting the essential information, so that a
solution to the decision-maker’s goals can be
obtained

15.  RESEARCH PHASE
o Operations and data collection for a better understanding of
the problems
o Formulation of hypothesis and model
o Observation and experimentation to test the hypothesis on
the basis of additional data
o Analysis of the available information and verification of the
hypothesis using pre-established measures of effectiveness
o Predictions of various results from the hypothesis
o Generalization of the various results and consideration of
alternative methods
 ACTION PHASE
o Making recommendations for the decision process by those
who first posed the problem for consideration, influencing
the operation in which the problem occurred

16.  Classification by degree of abstraction
o Language Models
o Concrete Models
 Classification according to structure
o Iconic (Physical) Model
o Analogue (Schematic) Model
o Symbolic Model
 Classification by purpose
o Descriptive Model
o Normative or Prescriptive Model

17.  Classification by nature of the environment
o Deterministic Models
o Probabilistic Models
 Classification according to behaviour
characteristics
o Static Models
o Dynamic Models
 Classification according to procedure of solution
o Analytical Models
o Simulation or Heuristic Models

18.  The number of assumptions made should be as
few as possible
 An O.R. model should take into account new
formulations without having any significant change
in its frame
 It should make minimum possible assumptions.
The model should accommodate a parametric type
of treatment.
 The model should be simple and coherent. The
number of variables utilized by it should be small
in number

19. 1. Formulation and definition of the problem
2. Construction of the model
3. Solution of the model
4. Testing the solution of the model
5. Establishing controls over the solution
6. Validation of the model
7. Implementation of the model

20. ISOLATION OF
MANAGEMENT
PROBLEM
QUALITATIVE
MODEL
(INFORMAL)
QUANTITATIVE
MODEL
(FORMAL)
TESTING
REAL WORLD
SYSTEM
PROBLEM
FORMULATION
MODEL
REFINEMENT
MODEL BUILDING
CONCLUSIONS
&
IMPLEMENTAT
ION
DATA
COLLECTION
MODEL TESTING
& SOLUTION
ESTABLISHING
CONTROLS &
SOLUTION
IMPLEMENTAT
ION

21.  Business Managers have to be explicit about their
objectives, assumptions and visualizing of constraints
 Decision maker can determine a solution to his routine
or repetitive problem
 Managers have to consider all those variables which
influence his decisions and the way these variables in a
problem interact with each other
 Decision maker can examine a situation from various
angles by simulating the model which he has
constructed for the real problem
 Allows decision maker to solve a complex problem
involving multiple variables much more quickly than if
he had to compute them using traditional methods
 OR techniques are gaining acceptance as they improve
manager’s decision making effectiveness

22.  OR approaches have to simplify the problem or make
simplifying assumptions in order to solve the problems
 Constructing complex OR model for solving problem is too
expensive
 OR model sometimes are not realistic
 Complex OR models can only be solved with the help of
computers
 Basic data are subjected to frequent changes incorporating
them in the OR model is a costly affair
 OR specialists forget to counsel the decision makers on the
limitations of OR models
 Magnitude of computation involved, lack of consideration
for non-quantifiable factors and psychological issues
involved in implementation are some of the other
shortcomings
 OR specialists are not decision makers themselves, they
provide a rational basis for decision making to executives

23.  Finance, Budgeting and Investments
a. Cash flow analysis, long-range capital requirements,
investment portfolios, dividend policies, etc
b. Credit policies, credit risks and delinquent account
procedures
c. Claim and complaint procedures
d. Dividend policies, investment and portfolio management,
balance sheet and cash flow analysis
 Purchasing, Procurement and Exploration
a. Determining the quantity and timing of purchase of raw
materials, machinery, etc.
b. Rules for buying and supplies under varying prices
c. Bidding policies
d. Equipment replacement policies
e. Determination of quantities and timings of purchases
f. Strategies for exploration and exploitation of new material
sources

24.  Production Management
i. Project Planning
a. Location and size of warehouses, distribution centres, retail
outlets, etc
b. Distribution Policy
ii. Manufacturing and Facility Planning
a. Production scheduling and sequencing
b. Project scheduling and allocation of resources
c. Selection and location of factories, warehouses and their sizes
d. Determining the optimal production mix
e. Maintenance policies and preventive maintenance
f. Scheduling and sequencing the production run by proper
allocation of machines
 Marketing Management
a. Product selection, timing, competitive actions
b. Advertising strategy and choice of different media of
advertising
c. Number of salesmen, frequency of calling of accounts, etc.

25. d. Effectiveness of market research
e. Size of the stock to meet the future demand
 Personnel Management
a. Recruitment policies and assignment of jobs
b. Selection of suitable personnel with due consideration for age and
skills, etc.
c. Establishing equitable bonus systems
 Research and Development
a. Determination of areas of concentration of research and
development
b. Reliability and evaluation of alternative changes
c. Control of development projects
d. Coordination of multiple research projects
e. Determination of time and cost requirements

26.  Allocation Models
 Assignment Models
 Decision Models
 Inventory Models
 Queuing Models
 Replacement Models
 Sequencing Models
 Network Scheduling Models
 Simulation Models
 Game Theory Models
 Markov – chain Models
 Combined OR Models