In linear programming, which term describes variables that can be controlled by the decision-maker?

In the context of linear programming, decision variables are indeed the elements that can be manipulated by the decision-maker to achieve the best outcome for the objective function. These variables represent the quantities to be determined within the constraints set by the problem. The objective of the linear programming model is to find the optimal values of these decision variables that will either maximize or minimize the objective function, which is typically a representation of cost, profit, or efficiency, depending on the specific scenario.

Understanding decision variables is crucial because they directly influence the results and effectiveness of the linear programming model. By adjusting these variables, a decision-maker can explore different solutions and determine the most effective approach to meet their goals. The other terms listed, such as constraint variables and objective variables, refer to different aspects of the linear programming model and do not pertain to the controllable elements used directly in decision-making.