This paper presents a new iterative approach to probabilistic robust controller design, which is an alternative to the recently proposed Subgradient Iteration Algorithm (SIA). In its original version [12] the SIA possesses the useful property of guaranteed convergence in a finite number of iterations, but requires that the radius of a non-empty ball contained in the solution set is known a-prio...

We revisit the pairwise kidney exchange problem established by Roth Sonmez and Unver [23]. Our goal, explained in terms of graph theory, is to find a maximum fractional matching on an undirected graph, that Lorenz-dominates any other fractional matching. The Lorenz-dominant fractional matching, which can be implemented as a lottery of integral matchings, is in some sense the fairest allocation ...

In order to solve problems of optimization, Swarm Intelligence (SI) algorithms are extensively becoming more popular. Many swarm intelligence based optimization techniques are present but most face problems like convergence problem and local minimization problem. In this paper, a hybrid optimization algorithm is proposed using fractional order Artificial Bee Colony (ABC) and Genetic Algorithm (...

We present an algorithm for computing the distance between two free-form surfaces. Using line geometry, the distance computation is reformulated as a simple instance of a surface-surface intersection problem, which leads to lowdimensional root finding in a system of equations. This approach produces an efficient algorithm for computing the distance between two ellipsoids, where the problem is r...

This paper presents an algorithm for computing the distance between two free-form surfaces. Using line geometry, the distance computation is reformulated as a simple instance of a surface-surface intersection problem, which leads to a low-dimensional root finding in a system of equations. This approach produces an efficient algorithm for computing the distance between two ellipsoids, where the ...

The accuracy of magnetic heading sensor is reduced by the impact of manufacturing technology and local magnetic interferences. The singularity of constraint matrix in traditional calibration algorithm leads to unstable results. Therefore, an improved least-square ellipsoid fitting method is proposed in this paper. The error source and the deviation mathematical model are introduced. On the basi...

This talk surveys applications of space dilation in the perceptron-like algorithms for solving systems of linear inequalities in polynomial time: from the ellipsoid algorithm to the modified perceptron algorithm and the perceptron rescaling algorithm. It also suggests a more general version of the latter algorithm and poses an open problem about the lowest complexity of this approach. Space dil...

This paper proposes a deep cut version of the ellipsoid algorithm for solving a general class of continuous convex programming problems. In each step the algoritbm does not require more computational effort to construct these deep cuts than its corresponding central cut version. Rules that prevent some of the numerical instabilities and theoretical drawbacks usually associated with the algorith...

In this paper, we will propose algorithms for calculating a minimal ellipsoid circumscribing a polytope defined by a system of linear inequalities. If we know all vertices of the polytope and its cardinality is not very large, we can solve the problem in an efficient manner by a number of existent algorithms. However, when the polytope is defined by linear inequalities, these algorithms may not...

We consider the problem of online convex optimization against an arbitrary adversary with bandit feedback, known as bandit convex optimization. We give the first Õ( √ T )-regret algorithm for this setting based on a novel application of the ellipsoid method to online learning. This bound is known to be tight up to logarithmic factors. Our analysis introduces new tools in discrete convex geometry.