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Applications of Operational Research (queuing theory)

Basics of Operational Research


Operations research (also referred to as decision science, or management science) is an interdisciplinary mathematical science that focuses on the effective use of technology by organizations. In contrast, many other science & engineering disciplines focus on technology giving secondary considerations to its use.
Employing techniques from other mathematical sciences — such as mathematical modeling, statistical analysis, and mathematical optimization — operations research arrives at optimal or near-optimal solutions to complex decision-making problems. Operations Research is often concerned with determining the maximum (of profit, performance, or yield) or minimum (of loss, risk, or cost) of some real-world objective.
Operational research encompasses a wide range of problem-solving techniques and methods applied in the pursuit of improved decision-making and efficiency. 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. 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
Problems addressed with OR are-
·        Critical path analysis or project planning: identifying those processes in a complex project which affect the overall duration of the project
·        Floorplanning: designing the layout of equipment in a factory or components on a computer chip to reduce manufacturing time (therefore reducing cost)

·        Bayesian search theory : looking for a target

·        Automation: automating or integrating robotic systems in human-driven operations processes.

QUEUEING MODEL

Adopting queuing theory to estimate network traffic becomes the important way of network performance prediction, analysis and estimation; through this we can imitate the true network, its reliable and useful for organizing, monitoring and defending the network.

In queuing theory, a queuing model is used to approximate a real queueing situation or system, so the queuing behavior can be analyzed mathematically. Queuing models allow a number of useful steady state performance measures to be determined, including:

  • the average number in the queue, or the system,
  • the average time spent in the queue, or the system,
  • the statistical distribution of those numbers or times,
  • the probability the queue is full, or empty, and
the probability of finding the system in a particular state

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