Operational research may have originated in the efforts of military planners during World War I (convoy theory and Lanchester's laws). Beginning in the 20th century, study of inventory management could be considered the origin of modern operations research with economic order quantity developed by Ford W. Charles Babbage's research into the cost of transportation and sorting of mail led to England's universal "Penny Post" in 1840, and to studies into the dynamical behaviour of railway vehicles in defence of the GWR's broad gauge. In the 17th century, mathematicians Blaise Pascal and Christiaan Huygens solved problems involving complex decisions ( problem of points) by using game-theoretic ideas and expected values others, such as Pierre de Fermat and Jacob Bernoulli, solved these types of problems using combinatorial reasoning instead. Since that time, operational research has expanded into a field widely used in industries ranging from petrochemicals to airlines, finance, logistics, and government, moving to a focus on the development of mathematical models that can be used to analyse and optimize complex systems, and has become an area of active academic and industrial research. In the decades after the two world wars, the tools of operations research were more widely applied to problems in business, industry, and society. Manufacturing, service sciences, and supply chain management.The major sub-disciplines in modern operational research, as identified by the journal Operations Research, are: Operational researchers faced with a new problem must determine which of these techniques are most appropriate given the nature of the system, the goals for improvement, and constraints on time and computing power, or develop a new technique specific to the problem at hand (and, afterwards, to that type of problem). Because of the computational and statistical nature of most of these fields, OR also has strong ties to computer science and analytics. Nearly all of these techniques involve the construction of mathematical models that attempt to describe the system. Operational research (OR) encompasses the development and the use of a wide range of problem-solving techniques and methods applied in the pursuit of improved decision-making and efficiency, such as simulation, mathematical optimization, queueing theory and other stochastic-process models, Markov decision processes, econometric methods, data envelopment analysis, neural networks, expert systems, decision analysis, and the analytic hierarchy process. Originating in military efforts before World War II, its techniques have grown to concern problems in a variety of industries. Operations research is often concerned with determining the extreme values of some real-world objective: the maximum (of profit, performance, or yield) or minimum (of loss, risk, or cost). Because of its emphasis on practical applications, operations research has overlap with many other disciplines, notably industrial engineering. Įmploying techniques from other mathematical sciences, such as modeling, statistics, and optimization, operations research arrives at optimal or near-optimal solutions to complex decision-making problems. The term management science is sometimes used as a synonym. It is sometimes considered to be a subfield of mathematical sciences. Operations research ( British English: operational research), often shortened to the initialism OR, is a discipline that deals with the development and application of advanced analytical methods to improve decision-making. ( December 2020) ( Learn how and when to remove this template message) The specific issue is: US perspective completely neglected, George Dantzig gets a passing mention only You may improve this article, discuss the issue on the talk page, or create a new article, as appropriate. The examples and perspective in this article may not represent a worldwide view of the subject.
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