NellyCookasked Jun 4, 2021 at 9:27am
In a linear programming model, variables are parameters that a user chooses to define the dependence. The decision variable is a concept used to emphasize that the values of variables influence the decision-making process. The decision variables are values that the user can control or requires information on the critical values that bring certain result for the process (e.g. maximum inflation rate). For instance, when the best value of a decision variable is reached, the problem is solved (or the decision is made). For practical problems, the decision variables represent economic activity (number of customers, tax rate, inflation rate) or the amount of raw material or resources required for the process. The consistent choice of the variables can reduce risks and increase profit (Dantzig & Thapa, 2003).
The objective function is the dependent variable. It depends on the decision variables. When the value of a decision variable changes, the value of the objective function consequently changes.
The objective function is a value calculated after optimization of the decision variables, maximized or minimized. The constraint refers to limitation in value that the decision variables can take. For many practical economical models, the general constraint is that most variables should be more than zero. Apparently, resources, prices, quantities take positive values. For some variables, the value can be less than zero (inflation rate). The constraints typically appear because of practical reasons, for example, limitation in personnel, space or money. Therefore, the constraints should be taken into consideration when the linear programming model is resolved, since the result needs to be achievable (Dantzig & Thapa, 2003).
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