Application of mathematical (quantitative) techniques to decision making. In OR, a problem is first clearly defined and represented (modeled) as a set of mathematical equations. It is then subjected to rigorous computer analysis to yield a solution (or a better solution) which is tested and re-tested against real-life situations until an optimum solution is found. OR applies different approaches to different types of problems: dynamic programming, linear programming, and critical path method are used in handling complex information in allocation of resources, inventory control, and in determining economic reorder quantity; forecasting and simulation techniques such as Monte Carlo method are used in situations of high uncertainty such as market trends, next period's sales revenue, and traffic patterns. Also called decision science, management science, or operational research. Operational research, also known as operations research, is an interdisciplinary branch of applied mathematics and formal science that uses advanced analytical methods such as mathematical modeling, statistical analysis, and mathematical optimization to arrive at optimal or near-optimal solutions to complex decision-making problems. It 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.[1]

|Contents | |[hide] | |1 Overview | |2 History | |2.1 Historical origins | |2.2 Second World War | |2.3 After World War II | |3 Problems addressed with operational research | |4 Management science | |4.1 Techniques | |4.2 Applications of management science | |5 Societies and journals | |6 See also | |7 Notes | |8 References | |9 Further reading | |10 External links |

[pic][edit] Overview

Operational research encompasses a wide range of problem-solving techniques and methods applied in the pursuit of improved decision-making and efficiency.[2] Some of the tools used by operational researchers are statistics, optimization, probability theory, queuing theory, game theory, graph theory, decision analysis, mathematical modeling and simulation. Because of the computational nature of these fields, OR also has strong ties to computer science. 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. Work in operational research and management science may be characterized as one of three categories:[3] • Fundamental or foundational work takes place in three mathematical disciplines: probability, optimization, and dynamical systems theory. • Modeling work is concerned with the construction of models, analyzing them mathematically, implementing them on...