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The term O.R. is somewhat unfortunate
or even funny, since OR is not (any more) concerned with
operations, nor does its application involve any research
in the traditional sense.
Some good Operations Research definitions
are:
-
Operations Research
is the discipline of applying advanced analytical methods to
help make better decisions. By using techniques such as mathematical
modeling to analyze complex situations, operations research gives
executives the power to make more effective decisions and build more
productive systems.
-
O.R.
is the professional discipline that deals with the application of
information technology for informed decision-making. It aims to
provide a rational bases for decision making by seeking to
understand and structure complex situations and to use this
understanding to predict system behavior and improve system
performance. Much of this work is done using analytical and
numerical techniques to develop and manipulate mathematical and
computer models of organizational systems composed of people,
machines, and procedures.
-
O.R.
draws upon ideas from engineering, management, mathematics, and
psychology to contribute to a wide variety of application domains;
the field is closely related to several other fields in the
"decision sciences" -- applied mathematics, computer science,
economics, industrial engineering, and systems engineering.
-
O.R.
is the science of rational decision making and the study, design and
integration of complex situations and systems with the goal of
predicting system behavior and improving or optimizing system
performance. It encompasses managerial decision making, mathematical
and computer modeling and the use of information technology for
informed decision-making.
As a science, O.R. traces its roots
back to World War II, as military planners
such as Frederick Lanchester and Patrick Blackett looked for ways to bring scientific calculations to Allied
warfare against Nazi Germany.
Typical Operations Research
methods include:
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Simulation - Giving you the ability to try out approaches and test ideas
for improvement
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Optimization - Narrowing your choices to the very best when there are
virtually innumerable feasible options and comparing them is difficult
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Probability and statistics
- Helping you measure risk, mine data to find
valuable connections and insights, test conclusions, and make reliable
forecasts
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Mathematical models
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(Complex) algorithms
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Visualization
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Neural networks
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Pattern recognition
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Data mining, Data warehousing
O.R. can be used for supporting an
indefinite number of business decisions. However, typical
applications of
Operations Research are:
-
Capital budgeting
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Asset allocation
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Portfolio selection
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Fraud prevention,
Anti-Money Laundering
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Benchmarking
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Marketing channel
optimization, Customer segmentation
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Direct marketing
campaigns, Predicting customer response, Campaign optimization
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Supply chain
planning
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Distribution,
Routing, Scheduling, Traffic flow optimization
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Resource allocation, Staff allocation
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Inventory planning
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Retail planning,
Merchandize optimization
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Product mix and
blending, Industrial waste reduction
Compare to Operations Research:
Simulation
| Benchmarking |
Regression Analysis |
Exponential Smoothing
| CAPM |
Real Options |
Game Theory
More management models
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