# Strict inequalities in LP

How should we deal with strict inequalities in a linear programming problem? For example:

inequalities such as $ax< b$;

• Add a tolerance, $\epsilon>0$ and try solving with $ax \leq b-\epsilon$. Commented Jul 20, 2012 at 7:57
• @copper.hat Does tha apply to answer below?
– BCLC
Commented Mar 3, 2016 at 3:40
• @BCLC: In general, there will be no solution if the inequality is strict. So, what you do depends on what you want. The $\epsilon$ trick will work, but if the constraint is active, then the solution will not necessarily be optimal for the original problem. Commented Mar 3, 2016 at 4:07

Consider the $1$-variable LPP: $Max$ $x$ subject to $x<3$. Now there does not exist any value of $x$ for which maximum is achieved and which lies in the feasible region.
• 1. Linear programs are not necessarily about optimization, they can also be about feasibility. 2. Replacing ‘$\max$’ with ‘$\sup$’ evades the technical issue you point out. Commented Jul 16, 2013 at 14:30
• $x \le 3 - \epsilon$ ?