• A constraint is binding if it satisfied as a strict equality in the optimal solution.
otherwise, it is non binding.
• the only way to change the level curve for the objective function is to change
the coefficients in the objective function (141)
• if you get sensitivity of 0 = you can get an alternate optimal solution (if they
exist) by adding a constraint to your model that holds the objective
function at the current optimal value, and then attempting to maximize or
minimize the value of one of the decision variables that had an objective
function coefficient with an allowable increase or decrease of 0.
• Shadow price: indicates the amount by which the objective function value
changes given a unit increase in the RHS value of the constraint,
assuming all other coefficients remain constant.
◦ positive: a unit increase in the RHS value of the associated constraint
results in an increase in the optimal objective function value
◦ negative: a unit increase in the RHS value of the associated constraint
results in a decrease in the optimal objective function value.
◦ they do not tell you which values the decision variables need to
assume in order to active this new objective function v