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Simulation
When decisions are to be taken under conditions of uncertainty, simulation can be used. Simulation as a quantitative method requires the setting up of a mathematical model which would represent the interrelationships between the variables involved in the actual situation in which a decision is to be taken. Then, a number of trials or experiments are conducted with the model to determine the results that can be expected when the variables assume various values. Simulation can therefore be defined as a procedure whereby one can draw conclusions about the behavior of a given system by examining the behavior of a corresponding model whose cause-effect relationships are similar to those in the actual system. There are a few basic concepts which must be understood before applying the simulating technique.
System: It is that segment to be studied or understood to draw conclusions. In the illustration given above, the market for the product together with the firms' production process constitute the relevant system. Only after the system is defined, can we identify the variables which interact with one another in the system and establish their relationships mathematically.
Decision Variables: A variable, as its name implies, may assume differing values under differing sets of circumstances. Decision variables are those variables whose value is to be determined through the process of simulation. In our illustration, the price to be charged by the firm for its product is the decision variable.
Environmental Variables: These are the variables which describe the environment and are dependent upon that environment in which the system is operating. In the illustration, competitors' average price, consumer preferences and demand, etc. are the environmental variables.
Endogenous Variables: Unlike the environmental variables these are generated within the system itself. In the illustration, quantity sold, sales revenue, total cost and profit are endogenous variables.
Criterion Function: One or more of the endogenous variables or some specified combination of these is used as the criterion function for evaluating the performance of the system. In the illustration, profit is used as the criterion function.
Examples of grouped, simple and frequency distribution data
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