OPERATIONS RESEARCH

Operations research, or operational research in British usage, is a discipline that deals with the application of advanced analytical methods to help make better decisions.[1] .

It is often considered to be a sub-field of mathematics.[2] The terms management science and decision science are sometimes used as synonyms.

EMPLOYING techniques from other mathematical sciences, such as mathematical modeling, statistical analysis, and mathematical optimization, operations research arrives at optimal or near-optimal solutions to complex decision-making problems.

Operations Research (OR) applies scientific method to the management of organized systems in business, industry, government and other enterprises.

OR is regularly applied in areas such as: supply chain management MARKETING and revenue management systems manufacturing plants FINANCIAL engineering telecommunication networks healthcare management transportation networks energy and the environment service systems web commerce military defense

Typically, applications of OR in these and other areas deal with decisions involved in planning the efficient allocation of scarce resources - such as material, skilled workers, machines, MONEY and time - to achieve stated goals and objectives under conditions of uncertainty and over a span of time.

Efficient allocation of resources may entail establishing policies, designing processes, or relocating assets. OR analysts solve such management decision problems with an array of mathematical methodologies.

To do this, OR professionals first represent the system in mathematical form. Rather than using trial and error on the system itself, they build an algebraic or computational model of the system and then manipulate or solve the model, using computers, to come up with the best decisions.

Often motivated by new decision problems, OR researchers work to improve and expand the applicable methodologies.

As OR professionals strive to construct models that accurately represent and forecast relationships, they may use statistical analysis. The system may be characterized by uncertainty and risk and so require use of probability analysis. Finding an efficient allocation of resources may EMPLOY optimization techniques that can deal with huge numbers of interrelated variables and constraints.

For many complex systems, the implications of a particular resource allocation strategy may only be understood by building a computer simulation of the system and testing an array of strategies against it.

Evaluating allocation strategies often requires an understanding of accounting and managerial finance.

Because of its emphasis on human-technology interaction and because of its focus on practical applications, operations research has overlap with other disciplines, notably industrial engineering and operations management, and draws on psychology and organization science.

Operations Research is known by different names in different organizations: Analytics, Systems Analysis and Management Science among them. Related fields include Operations Management, Industrial Engineering, and Systems Engineering (OR tends to have a broader and more mathematical scope than these fields).

Information lies at the core of what OR analysts do: they collect, synthesize, and work with information, and use information systems as a source of data and a means of implementing solutions.

For this reason, Cornell’s School of OR&IE has changed the “I” in their name, from “Industrial” to “Information,” to become the School of Operations Research and Information Engineering.

Operations research is often concerned with determining the maximum (of profit, performance, or yield) or minimum (of loss, risk, or cost) of some real-world objective.

Originating in military efforts before World War II, its techniques have grown to concern problems in a variety of industries.[4]

Introduction It had its early roots in WorldWar II and is flourishing in business and industry with the aid of Computers.

Operations : The activities carried out in an organization.

Research .The process of observation and testing characterized by the scientific method. Situation, problem statement, model construction, validation, experimentation, candidate solutions.

The modern field of operational research arose during World War II. In the World War II era, operational research was defined as "a scientific method of providing executive departments with a quantitative basis for decisions regarding the operations under their control.

During the Second World War close to 1,000 men and women in Britain were engaged in operational research.

About 200 operational research scientists worked for the British Army.

Patrick Blackett worked for several different organizations during the war. Early in the war while working for the Royal Aircraft Establishment (RAE), he set up a team known as the "Circus" which helped to reduce the number of anti-aircraft artillery rounds needed to shoot down an enemy aircraft from an average of over 20,000 at the start of the Battle of Britain to 4,000 in 1941.[15]

Operations Research is a quantitative approach to decision making based on the scientific method of problem solving.

The British/Europeans refer to “Operational Research", the Americans to “Operations Research" - but both are often shortened to just "OR". •

Another term used for this field is “Management Science" ("MS").

In U.S. OR and MS are combined together to form "OR/MS" or "ORMS".

• Yet other terms sometimes used are “Industrial Engineering" ("IE") and “Decision Science" ("DS").

Terminology In Industry Business Government Defense fields People Machine Material

More complete data Consideration of all available options Careful predictions of outcomes and estimates of risk

The latest decision tools and techniques .

This Situation Provides Optimization is a word that comes to

mind first in operations research.

• 7 Steps of Problem Solving

(First 5 steps are the process of decision making) –

Identify and define the problem. Determine the set of alternative

solutions. Determine the criteria for evaluating the

alternatives. Evaluate the alternatives. Choose an alternative.

Implement the chosen alternative. Evaluate the results. Problem Solving and Decision Making

Management Science Approach Observation • Identification of a problem that exists in the system or organization.

“Right solution” can not be obtained from the “wrong problem.

The first and most important stage of the work is defining the problem well. .

This phase helps examine the problem at hand quantitatively.

Identification Of The Problem

The Establishment Of The Model Development of the functional mathematical relationships that describe-

Decision variables Objective function Constraints of the problem and Non negativity condition

Generally, experimenting with models (compared to experimenting with the real situation): – requires less time – is less expensive – involves less risk

Advantages of Models :

Obtaining Model Solution This phase obtains an optimal solution for the model by using various techniques.

1. Linear Programming Problem (LPP) 2. Transportation Problem (TP) 3. Assignment Problem (AP) 4. Simulation 5. PERT/CPM Various Techniques/Methods

Before the application of the model solution, the validity of model and reliability of the solution should be tested. Validity of the model can be decided by comparing its outputs with the results of past. Testing Of The Model Solution

If past behavior is repeated when provided similar inputs (a stable solution is being obtained), the model will be valid.

A solution to a problem usually implies changes for some individuals in the organization Implementation of the solution obtained from a validated model is a reliable solution to the real- life problems Implementation Situation Procedure Implement the Procedure

CONCLUSION : Operation research ensures the effective working of organizations by providing solutions to their various problems.