in many applications, ranking of decision making units (dmus) is a problematic technical task procedure to decision makers in data envelopment analysis (dea), especially when there are extremely efficient dmus. in such cases, many dea models may usually get the same efficiency score for different dmus. hence, there is a growing interest in ranking techniques yet. the purpose of this paper is ra...

Recently, infeasibility issues in interior methods for nonconvex nonlinear programming have been studied. In particular, it has been shown how many line-search interior methods may converge to an infeasible point which is on the boundary of the feasible region with respect to the inequality constraints. The convergence is such that the search direction does not tend to zero, but the step length...

We investigate infeasibility issues arising along network design for information-theoretically secure cryptography. In particular, we consider the problem of communication in perfect privacy and formally relate it to graph augmentation problems and the P-vs-NP-question. Based on a game-theoretic privacy measure, we consider two optimization problems related to secure infrastructure design with ...

In a recent paper, Birgin, Floudas and Mart́ınez introduced an augmented Lagrangian method for global optimization. In their approach, augmented Lagrangian subproblems are solved using the αBB method and convergence to global minimizers was obtained assuming feasibility of the original problem. In the present research, the algorithm mentioned above will be improved in several crucial aspects. On...

In principle, higher-order networks that have multiple edge types are more informative than their lower-order counterparts. In practice, however, excessively rich information may be algorithmically infeasible to extract. It requires an algorithm that assumes a high-dimensional model and such an algorithm may perform poorly or be extremely sensitive to the initial estimate of the model parameter...

A novel matching based heuristic algorithm designed to detect specially formulated infeasible {0, 1} IPs is presented. The algorithm's input is a set of nested doubly stochastic subsystems and a set E of instance defining variables set at zero level. The algorithm deduces additional variables at zero level until either a constraint is violated (the IP is infeasible), or no more variables can be...

We suppose the existence of an oracle which is able to solve any semidefinite programming (SDP) problem having interior feasible points at both its primal and dual sides. We note that such an oracle might not be able to directly solve general SDPs even after certain regularization schemes such as facial reduction or Ramana’s dual are applied. The main objective of this work is to fill this gap ...

Hierarchical production planning (HPP) is a well-known approach to cope with the complexity of multi-level production planning and scheduling problems in real-world industrial cases. However, negligence of some issues such as inherent uncertainty in critical input data (i.e., market demands, production capacity and unit costs) as well as possible infeasibility of these problems due to imposing ...

This paper considers the problem of minimizing a linear function over the intersection of an aane space with a closed convex cone. In the rst half of the paper, we give a detailed study of duality properties of this problem and present examples to illustrate these properties. In particular, we introduce the notions of weak/strong feasibility or infeasibility for a general primal-dual pair of co...