Operations Research


Management deals with reality that is at once complex, dynamic, and multifaceted. It is neither possible nor desirable, to consider each and every element of reality before deciding the courses of action. It is impossible because of time available to decide the courses of action and the resources, which are limited in nature. More over in many cases, it will be impossible for a manager to conduct experiment in real environment.


Methods of Solving Operations Research Problems

There are three methods of solving an operations research problem. They are:

1.                   Analytical method,

2.                   Iterative Method,

3.                   The Monte-Carlo Technique.

Analytical Method:When we use mathematical techniques such as differential calculus, probability theory etc. to find the solution of a given operations research model, the method of solving is known as analytical method and the solution is known as analytical solution. Examples are problems of inventory models. This method evaluates alternative policies


Iterative Method (Numerical Methods):This is trial and error method. When we have large number of variables, and we cannot use classical methods successfully, we use iterative process. First, we set a trial solution and then go on changing the solution under a given set of conditions, until no more modification is possible. The characteristics of this method is

that the trial and error method used is laborious, tedious, time consuming and costly. The solution we get may not be accurate one and is approximate one. Many a time we find that

after certain number of iterations, the solution cannot be improved and we have to accept it

as the expected optimal solution.

Monte-Carlo Method:This method is based on random sampling of variable's values from a distribution of the variable. This uses sampling technique. A table of random numbers must be available to solve the problems. In fact it is a simulation process.