Using standard nonlinear programming (NLP) theory, we establish formulas for first and second order directional derivatives for optimal value functions of parametric mathematical ...
Several combinatorial optimization problems choose elements to minimize the total cost of constructing a feasible solution that satisfies requirements of clients. In the STEINER T...
We show how to approximate the feasible region of structured convex optimization problems by a family of convex sets with explicitly given and efficient (if the accuracy of the ap...
: A general framework for solving combinatorial optimization problems heuristically by the Ant System approach is developed. The framework is based on the concept of a construction...
We propose the first combinatorial solution to one of the most classic problems in combinatorial optimization: the generalized minimum cost flow problem (flow with losses and g...