I am reading a paper on solving a problem using LP methods, it says
"The linear problem has $n$ variables and $m$ constraints. From linear programming theory, we know that there is an optimal solution at which the number of constraints having equality is no smaller than the number of variables"
- Does the "$m$ constraints" include equality constraints as well? I mean, if there are more than $n$ equality constraints, does that statement tell nothing meaningful?
- Why the # of equality must be $\ge n$? Can anyone easily explain it or suggest some materials? I am new to LP optimization or convex optimization.