The change in objective function value for unit will increase in coefficient of decision variable.

The reduced cost is a measure of how much the objective function value would improve by increasing the value of a non-basic variable in a minimization problem. It helps guide the simplex algorithm towards finding the optimal solution by identifying variables that can be added to the basis to improve the objective function.

The coefficient of a decision variable 

Decreased costs are a crucial diagnostic tool for linear programming, especially in iterative algorithms like the Simplex method. They allow for the alteration of non-basic variables from their current value, providing insight into the change in the objective function. These costs are particularly useful for understanding the evolution of the objective function, making them a vital diagnostic tool in linear programming.

refers to the amount by which the objective function coefficient of a non-basic variable needs to be decreased in order to include it in the current solution. It represents the potential improvement in the objective function value if the corresponding variable is allowed to enter the solution.