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Operations Research

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Operations Research

Operation Research is an interdisciplinary branch of Mathematical Science. It uses methods like Mathematical modeling, Statistics, and Algorithms to arrive at optimal and excellent decisions in complex problems which are otherwise highly difficult or nearly impossible to achieve using mere common sense. The final objective behind using operations research is to bring out a best possible solution to a problem mathematically, which excels or optimizes the performance of the system.
“Operations Research as the application of scientific methods, techniques and tools to operation of a system with optimum solutions to the problems.” Here optimum implies the one, which is best of all possible alternatives.

Scope of Operations Research


The application of operations research methods helps in making decisions in such complicated situations. A few example of application in which operations research is currently used include:

 

  • Designing the layout of factory for efficient flow of materials.
  • Constructing a telecommunication network at low cost while still guaranteeing quality of service.
  • Road traffic management and one way street allocations.
  • Designing the layout of computer chip to reduce manufacturing time and hence reducing the cost.

Significant Features of Operations Research

  • Decision making: A major basis of OR is that decision making can be considered as a general systematic process that consists of the following steps:
  • Define the problem and establish the criterion which will be used.
  • Select the alternative courses of action for consideration.
  • Determine the model to be used and the values of the parameters of the process.
  • Evaluate the alternatives and choose the one, which is optimum.
  • Scientific approach: OR employs systematic methods for the purpose of solving problems. It is a distinguished process of reasoning and consists of the following steps:
  • The problem can be analyzed is defined clearly and the conditions for the observations are to be determined.
  • Observations are made under unstable conditions to determine the performance of the system.
  • On the bases of observations, a theory describing how the various factors involved are believed to interact and the best solution to the problem is formulated.
  • To test the theory, an experiment is designed and executed. Observations are made and dimensions are recorded.

Finally, the results of the experiments are analyzed and the theory is either accepted or rejected. If the theory is accepted, the best solution to the problem is obtained.
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SIMULATION Simulation involves developing a model of some real event and then performing experiments on the model evolved.
PROCESS OF SIMULATION There are four phases of the simulation process.

  • Definition of the problem and statement of objectives.
  • Building of a suitable model.
  • Experiments with the model constructed.
  • Evaluation of the results of simulation.

APPLICATION OF SIMULATION

  • The application of simulation in business is extremely wide. Unlike the other mathematical models, through theoretical, simulation can be easily understood by the users and thereby facilitates their active e involvement.
  • Simulation can also be used for a wide diversity of problem encountered in production systems.
  • Like in the case of other OR models, with the help of simulation, the manager tries to strike a balance between opposing costs of providing facilities and the opportunity and other costs f not providing them.

ADVANTAGES AND DISADVANTAGES OF SIMULATION

  • Simulation approach is known as a powerful tool for management decision making. This does not mean that one should ignore the cost associated with a simulation study for data collection, formation of the model and the computer time.
  • A simulation application is based on the hypothesis that the behavior pattern of relevant variables is known, and this very hypothesis sometimes becomes questionable.
  • The chief advantage of the simulation technique is its capacity to lend itself to problems that are cumbersome, or impossible to handle mathematically using logical methods.
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