Week 4 Discussion Questions
1. Many times, linear optimization is used to maximize an objective function because profit, productivity, or efficiency is the outcome of interest. Provide two examples where the goal is to optimize a process by minimizing an objective function. In your examples, identify the outcome and any constraints that would need to be met.
2. When many constraints are present in a linear optimization problem, there is a greater chance that a redundant constraint exists. Assume you are trying to maximize an objective function and you have two decision variables, X1 and X2. If a redundant constraint exists, does the constraint become necessary if you try to minimize (instead of maximize) the same objective function? Why? Do you need an objective function to determine if a constraint is redundant? Explain.
