Operations research, often shortened to the abbreviation OR, is a discipline that deals with the application and development of advanced analytical methods for the improvement of decision-making. It is also sometimes referred to as a subfield of mathematical sciences and is also sometimes called management science.
Operations research uses techniques from other mathematical sciences like modeling, statistics, or optimization, and arrives at optimal or close to optimal solutions to complex decision-making problems. Since it emphasizes a great deal on practical applications, operations research often overlaps with many other disciplines, especially in the realm of industrial engineering. It is often concerned with the determination of extreme values of some real-world objective like the maximum performance, yield, or profit, or minimum risk, cost, or loss. Even though operations research orfiginated in military efforts before World War II, the techniques used in the same have grown to concern problems in a number of industries.
It encompasses the development and use of a range of methods and problem-solving techniques and are applied in the pursuit of improved decision-making and efficiency, like in the case of:
- Simulation
- Mathematical optimization
- Queueing theory and other stochastic-process models
- Markov decision processes
- Econometric methods
- Data envelopment analysis
- Neural networks
- Expert systems
- Decision analysis,
- Analytic hierarchy process
Almost all of these techniques involve constructing mathematical models that attempt to describe the system. Since there is a statistical and computational nature for most of these fields, OR has strong links to computer science and analytics.
The main sub-disciplines of modern operational research are as follows:
- Computing and information technologies
- Financial engineering
- Manufacturing, service sciences, and supply chain management
- Policy modeling and public sector work
- Revenue management
- Simulation
- Stochastic models
- Transportation
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