17 research outputs found
Sharp Bounds on Davenport-Schinzel Sequences of Every Order
One of the longest-standing open problems in computational geometry is to
bound the lower envelope of univariate functions, each pair of which
crosses at most times, for some fixed . This problem is known to be
equivalent to bounding the length of an order- Davenport-Schinzel sequence,
namely a sequence over an -letter alphabet that avoids alternating
subsequences of the form with length
. These sequences were introduced by Davenport and Schinzel in 1965 to
model a certain problem in differential equations and have since been applied
to bounding the running times of geometric algorithms, data structures, and the
combinatorial complexity of geometric arrangements.
Let be the maximum length of an order- DS sequence over
letters. What is asymptotically? This question has been answered
satisfactorily (by Hart and Sharir, Agarwal, Sharir, and Shor, Klazar, and
Nivasch) when is even or . However, since the work of Agarwal,
Sharir, and Shor in the mid-1980s there has been a persistent gap in our
understanding of the odd orders.
In this work we effectively close the problem by establishing sharp bounds on
Davenport-Schinzel sequences of every order . Our results reveal that,
contrary to one's intuition, behaves essentially like
when is odd. This refutes conjectures due to Alon et al.
(2008) and Nivasch (2010).Comment: A 10-page extended abstract will appear in the Proceedings of the
Symposium on Computational Geometry, 201
Degrees of nonlinearity in forbidden 0â1 matrix problems
AbstractA 0â1 matrix A is said to avoid a forbidden 0â1 matrix (or pattern) P if no submatrix of A matches P, where a 0 in P matches either 0 or 1 in A. The theory of forbidden matrices subsumes many extremal problems in combinatorics and graph theory such as bounding the length of DavenportâSchinzel sequences and their generalizations, Stanley and Wilfâs permutation avoidance problem, and TurĂĄn-type subgraph avoidance problems. In addition, forbidden matrix theory has proved to be a powerful tool in discrete geometry and the analysis of both geometric and non-geometric algorithms.Clearly a 0â1 matrix can be interpreted as the incidence matrix of a bipartite graph in which vertices on each side of the partition are ordered. FĂŒredi and Hajnal conjectured that if P corresponds to an acyclic graph then the maximum weight (number of 1s) in an nĂn matrix avoiding P is O(nlogn). In the first part of the article we refute of this conjecture. We exhibit nĂn matrices with weight Î(nlognloglogn) that avoid a relatively small acyclic matrix. The matrices are constructed via two complementary composition operations for 0â1 matrices. In the second part of the article we simplify one aspect of Keszegh and Genesonâs proof that there are infinitely many minimal nonlinear forbidden 0â1 matrices. In the last part of the article we investigate the relationship between 0â1 matrices and generalized DavenportâSchinzel sequences. We prove that all forbidden subsequences formed by concatenating two permutations have a linear extremal function
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Compaction and Separation Algorithms for Non-Convex Polygons and Their Applications
Given a two dimensional, non-overlapping layout of convex and non-convex polygons, compaction can be thought of as simulating the motion of the polygons as a result of applied "forces." We apply compaction to improve the material utilization of an already tightly packed layout. Compaction can be modeled as a motion of the polygons that reduces the value of some functional on their positions. Optimal compaction, planning a motion that reaches a layout that has the global minimum functional value among all reachable layouts, is shown to be NP-complete under certain assumptions. We first present a compaction algorithm based on existing physical simulation approaches. This algorithm uses a new velocity-based optimization model. Our experimental results reveal the limitation of physical simulation: even though our new model improves the running time of our algorithm over previous simulation algorithms, the algorithm still can not compact typical layouts of one hundred or more polygons in a reasonable amount of time. The essential difficulty of physical based models is that they can only generate velocities for the polygons, and the final positions must be generated by numerical integration. We present a new position-based optimization model that allows us to calculate directly new polygon positions via linear programming that are at a local minimum of the objective. The new model yields a translational compaction algorithm that runs two orders of magnitude faster than physical simulation methods. We also consider the problem of separating overlapping polygons using a minimal amount of motion and show it to be NP-complete. Although this separation problem looks quite different from the compaction problem, our new model also yields an efficient algorithm to solve it. The compaction/separation algorithms have been applied to marker making: the task of packing polygonal pieces on a sheet of cloth of fixed width so that total length is minimized. The compaction algorithm has improved cloth utilization of human generated pants markers. The separation algorithm together with a database of human-generated markers can be used for automatic generation of markers that approach human performance.Engineering and Applied Science
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Compaction Algorithms for Non-Convex Polygons and Their Applications
Given a two-dimensional, non-overlapping layout of convex and non-convex polygons, compaction refers to a simultaneous motion of the polygons that generates a more densely packed layout. In industrial two-dimensional packing applications, compaction can improve the material utilization of already tightly packed layouts. Efficient algorithms for compacting a layout of non-convex polygons are not previously known. This dissertation offers the first systematic study of compaction of non-convex polygons. We start by formalizing the compaction problem as that of planning a motion that minimizes some linear objective function of the positions. Based on this formalization, we study the complexity of compaction and show it to be PSPACE-hard. The major contribution of this dissertation is a position-based optimization model that allows us to calculate directly new polygon positions that constitute a locally optimum solution of the objective via linear programming. This model yields the first practically efficient algorithm for translational compaction-compaction in which the polygons can only translate. This compaction algorithm runs in almost real time and improves the material utilization of production quality human-generated layouts from the apparel industry. Several algorithms are derived directly from the position-based optimization model to solve related problems arising from manual or automatic layout generation. In particular, the model yields an algorithm for separating overlapping polygons using a minimal amount of motion. This separation algorithm together with a database of human-generated markers can automatically generate markers that approach human performance. Additionally, we provide several extensions to the position-based optimization model. These extensions enables the model to handle small rotations, to offer the flexible control of the distances between polygons and to find optimal solution to two-dimensional packing of non-convex polygons. This dissertation also includes a compaction algorithm based on existing physical simulation approaches. Although our experimental results showed that it is not practical for compacting tightly packed layouts, this algorithm is of interest because it shows that the simulation can speed up significantly if we use geometrical constraints to replace physical constraints. It also reveals the inherent limitations of physical simulation algorithms in compacting tightly packed layouts. Most of the algorithms presented in this dissertation have been implemented on a SUN SparcStationTM and have been included in a software package licensed to a CAD company.Engineering and Applied Science
Large bichromatic point sets admit empty monochromatic 4-gons
We consider a variation of a problem stated by ErdËos
and Szekeres in 1935 about the existence of a number
fES(k) such that any set S of at least fES(k) points in
general position in the plane has a subset of k points
that are the vertices of a convex k-gon. In our setting
the points of S are colored, and we say that a (not necessarily
convex) spanned polygon is monochromatic if
all its vertices have the same color. Moreover, a polygon
is called empty if it does not contain any points of
S in its interior. We show that any bichromatic set of
n â„ 5044 points in R2 in general position determines
at least one empty, monochromatic quadrilateral (and
thus linearly many).Postprint (published version