Robust optimal solutions in interval linear programming with forall-exists quantifiers
arXiv:1403.7427 · doi:10.1016/j.ejor.2016.04.032
Abstract
We introduce a novel kind of robustness in linear programming. A solution x* is called robust optimal if for all realizations of objective functions coefficients and constraint matrix entries from given interval domains there are appropriate choices of the right-hand side entries from their interval domains such that x* remains optimal. we propose a method to check for robustness of a given point, and also recommend how a suitable candidate can be found. We also discuss topological properties of the robust optimal solution set. We illustrate applicability of our concept in a transportation problem.
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Cited by in corpus (4)
- AE solutions and AE solvability to general interval linear systems
- A robust BFGS algorithm for unconstrained nonlinear optimization problems
- Testing weak optimality of a given solution in interval linear programming revisited: NP-hardness proof, algorithm and some polynomial cases
- AE regularity of interval matrices