Abstract
This paper deals with the problem of linear programming with inexact data represented by real intervals. We extend the concept of duality gap (DG), the difference between the primal and its dual optimal value, into interval linear programming (ILP).
We give characterizations of strongly- and weakly-zero DG in ILP and its special case where the matrix of coefficients is real. We show computational complexity of testing weakly- and strongly-zero DG for commonly used types of ILP.