Operational Research.Doc
Definition
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
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
References: [edit] History [edit] Early History (1940’s and 50’s) [edit] Modern Simulation (1980’s-present) Advances in technology in the 1980’s made the computer more affordable and more capable than they were in previous decades [18] which facilitated the rise of computer gaming