A constant-time parallel algorithm for computing convex hulls

The convex hull of a finite set of points in the plane can be computed in constant time using a polynomial number of processors.This work was supported by the Natural Sciences and Engineering Research Council of Canada under Grant NSERC - A3336.     

Group decisions I. In arbitrary spaces of fuzzy binary relations

This article solves the problem of finding a set of group decisions that satisfy the classical Pareto unanimity principle for the case of initial data represented as fuzzy relations of individual preference. The solution proceeds from results obtained in studying the structure of convex (in the sense defined here) sets and their convex hulls. In the first part that study is carried out for spaces of arbitrary fuzzy binary relations.     

Best Approximation and Perturbation Property in Hilbert Spaces

We study the perturbation property of best approximation to a set defined by an abstract nonlinear constraint system. We show that, at a normal point, the perturbation property of best approximation is equivalent to an equality expressed in terms of normal cones. This equality is related to the strong conical hull intersection property. Our results generalize many known results in the literature on perturbation property of best approximation established for a set defined by a finite system of linear/nonlinear inequalities. The connection to minimization problem is considered.The authors thank the referees for valuable suggestions.K.F. Ng - This author was partially supported by Grant A0324638 from the National Natural Science Foundation of China and Grants (2001) 01GY051-66 and SZD0406 from Sichuan Province. Y.R. He -This author was supported by a Direct Grant (CUHK) and an Earmarked Grant from the Research Grant Council of Hong Kong.     

Cover and Bounded Parallel Faces

We use the cover or the closure of the cover in order to determine when two disjoint closed convex sets have parallel faces, one of them being bounded. Moreover, we show that the study of the closure of the cover gives interesting results about the cover itself.     

On the Hardness of Computing Intersection,Union and Minkowski Sum of Polytopes

For polytopes P ₁,P ₂⊂ℝ ^d , we consider the intersection P ₁∩P ₂, the convex hull of the union CH(P ₁∪P ₂), and the Minkowski sum P ₁+P ₂. For the Minkowski sum, we prove that enumerating the facets of P ₁+P ₂ is NP-hard if P ₁ and P ₂ are specified by facets, or if P ₁ is specified by vertices and P ₂ is a polyhedral cone specified by facets. For the intersection, we prove that computing the facets or the vertices of the intersection of two polytopes is NP-hard if one of them is given by vertices and the other by facets. Also, computing the vertices of the intersection of two polytopes given by vertices is shown to be NP-hard. Analogous results for computing the convex hull of the union of two polytopes follow from polar duality. All of the hardness results are established by showing that the appropriate decision version, for each of these problems, is NP-complete.     

Network flows and non-guillotine cutting patterns

Up till now there has been no exact and effective algorithm for the problem of finding optimal cutting patterns of rectangles which are not restricted to those with the ‘guillotine’ property. This problem can be interpreted in a resource constrained scheduling context. The contribution of this paper to this topic is a good characterization of the flow functions and graphs corresponding to cutting patterns.     

A Note on Pluripolar Hulls of Graphs of Blaschke Products

In the paper we study the problem of characterization of pluripolar hulls of a class of functions containing Blaschke products. Mathematics Subject Classifications (2000) 32U30, 31A15, 30D50.Research partially supported by the KBN grant No. 5 P03A 033 21 and the Rectors Scholarship Fund at the Jagiellonian University.     

Limiting -subgradient characterizations of constrained best approximation

In this paper, we show that the strong conical hull intersection property (CHIP) completely characterizes the best approximation to any x in a Hilbert space X from the set

K:=C∩{xX:-g(x)S},