This document provides an overview of operational research. It defines operational research as applying scientific methods to optimize systems. The key approaches include orientation, problem definition, data collection, model formulation, model solution, validation, and implementation. Common techniques are linear programming, dynamic programming, queueing theory, inventory control, decision theory, network analysis, and simulation. These have been used across industries, defense, planning, agriculture, and public utilities. Overall, operational research is a tool that can improve productivity by optimizing systems through scientific problem solving.
3. 1. Introduction
Definition of Operation Research : the application
of scientific methods, techniques and tools to
problems involving the operations of a system so
as to provide those in control of the system with
optimum solutions to problems.
O.R. takes tool from subjects like statistics,
mathematics, engineering, economics,
psychology etc. and uses them to know the
consequences of possible alternative actions
5. ? Orientation : The primary objective of this step is to
constitute the team that will address the problem at hand
and ensure that all its members have a clear picture of
the relevant issues.
? Problem definition : The objective here is to further refine
the deliberations from the orientation phase to the point
where there is a clear definition of the problem in terms of
its scope and the results desired.
? Data Collection : process data is collected with the
objective of translating the problem defined in the
second phase into a model that can then be objectively
analyzed. Data typically comes from two sources ¨C
observation and standards.
6. ? Model Formulation : This definition implies that modeling is the
process of capturing selected characteristics of a system or a
process and then combining these into an abstract representation
of the original.
Models may be broadly classified into four categories:
1. Physical Models
2. Analogical Models
3. Computer Simulation Models
4. Mathematical Models
? Model Solution : the solution of the problem represented by the
model
7. ? Validation and Analysis :
1. The first is to verify that the solution itself makes sense. The
process of ensuring that the model is an accurate
representation of the system is called validation and this
is something that (whenever possible) should be done
before actual solution
2. The second step is process is referred to as postoptimality
analysis, or in layperson's terms. the solution obtained is
(a) a selective abstraction of the original system, and (b)
constructed using data that in many cases is not 100%
accurate.
8. ? Implementation and Monitoring : to implement
the final recommendation and establish control
over it. Implementation entails the constitution of a
team whose leadership will consist of some of the
members on the original O.R. team.
9. 3. Techniques of Operation Research
? Linear programming- It has been used to solve problems involving
assignment of jobs to machines, blending, product mix, advertising
media selection, least cost diet, distribution, transportation and
many others.
? Dynamic programming- It has been applied to capital budgeting,
selection of advertising media, cargo loading and optimal routing
problems.
? Waiting line or queuing theory- It has been useful to solve problems
of traffic congestion, repair and maintenance of broken-down
machines, number of service facilities, scheduling and control of
air-traffic, hospital operations, counter in banks and railway
booking agencies.
? Inventory control / planning- These models have been used to
determine economic order quantities, safety stocks, reorder levels,
minimum and maximum stock level.
10. ? Decision theory- It has been helpful in controlling hurricuanes,
water pollution, medicine, space exploration, research and
development projects.
? Network analysis (PERT& CPM)- These techniques have been used
in planning, scheduling and controlling construction of dams,
brides, roads and highways and development & production of
aircrafts, ships, computers etc.
? Simulation- It has been helpful in a wide variety of probabilistic
marketing situations.
? Theory of replacement- It has been extensively employed to
determine the optimum replacement interval for three types of
replacement problems:
i) Items that deteriorate with time.
ii) Items that do not deteriorate with time but fail suddenly.
iii) Staff replacement and recruitment.
11. 4. Operation research in the real
world
? Industry
? Defense
? Planning
? Agriculture
? Public utilities
12. 5. Summary
From the standpoint of an industrial engineer, O.R. is a tool
that can do a great deal to improve productivity. It should
be emphasized that O.R. is neither esoteric nor impractical,
and the interested I.E. is urged to study this topic further for
its techniques as well as its applications; the potential
rewards can be enormous.