Replacement Paths via Row Minima of Concise Matrices

Matrix $M$ is {\em $k$-concise} if the finite entries of each column of $M$ consist of $k$ or less intervals of identical numbers. We give an $O(n+m)$-time algorithm to compute the row minima of any $O(1)$-concise $n\times m$ matrix. Our algorithm yields the first $O(n+m)$-time reductions from the replacement-paths problem on an $n$-node $m$-edge undirected graph (respectively, directed acyclic graph) to the single-source shortest-paths problem on an $O(n)$-node $O(m)$-edge undirected graph (respectively, directed acyclic graph). That is, we prove that the replacement-paths problem is no harder than the single-source shortest-paths problem on undirected graphs and directed acyclic graphs. Moreover, our linear-time reductions lead to the first $O(n+m)$-time algorithms for the replacement-paths problem on the following classes of $n$-node $m$-edge graphs (1) undirected graphs in the word-RAM model of computation, (2) undirected planar graphs, (3) undirected minor-closed graphs, and (4) directed acyclic graphs.Comment: 23 pages, 1 table, 9 figures, accepted to SIAM Journal on Discrete Mathematic

Smooth heaps and a dual view of self-adjusting data structures

We present a new connection between self-adjusting binary search trees (BSTs) and heaps, two fundamental, extensively studied, and practically relevant families of data structures. Roughly speaking, we map an arbitrary heap algorithm within a natural model, to a corresponding BST algorithm with the same cost on a dual sequence of operations (i.e. the same sequence with the roles of time and key-space switched). This is the first general transformation between the two families of data structures. There is a rich theory of dynamic optimality for BSTs (i.e. the theory of competitiveness between BST algorithms). The lack of an analogous theory for heaps has been noted in the literature. Through our connection, we transfer all instance-specific lower bounds known for BSTs to a general model of heaps, initiating a theory of dynamic optimality for heaps. On the algorithmic side, we obtain a new, simple and efficient heap algorithm, which we call the smooth heap. We show the smooth heap to be the heap-counterpart of Greedy, the BST algorithm with the strongest proven and conjectured properties from the literature, widely believed to be instance-optimal. Assuming the optimality of Greedy, the smooth heap is also optimal within our model of heap algorithms. As corollaries of results known for Greedy, we obtain instance-specific upper bounds for the smooth heap, with applications in adaptive sorting. Intriguingly, the smooth heap, although derived from a non-practical BST algorithm, is simple and easy to implement (e.g. it stores no auxiliary data besides the keys and tree pointers). It can be seen as a variation on the popular pairing heap data structure, extending it with a "power-of-two-choices" type of heuristic.Comment: Presented at STOC 2018, light revision, additional figure

Work-Optimal Parallel Minimum Cuts for Non-Sparse Graphs

We present the first work-optimal polylogarithmic-depth parallel algorithm for the minimum cut problem on non-sparse graphs. For $m\geq n^{1+\epsilon}$ for any constant $\epsilon>0$, our algorithm requires $O(m \log n)$ work and $O(\log^3 n)$ depth and succeeds with high probability. Its work matches the best $O(m \log n)$ runtime for sequential algorithms [MN STOC 2020, GMW SOSA 2021]. This improves the previous best work by Geissmann and Gianinazzi [SPAA 2018] by $O(\log^3 n)$ factor, while matching the depth of their algorithm. To do this, we design a work-efficient approximation algorithm and parallelize the recent sequential algorithms [MN STOC 2020; GMW SOSA 2021] that exploit a connection between 2-respecting minimum cuts and 2-dimensional orthogonal range searching.Comment: Updates on this version: Minor corrections for the previous and our resul

Approximated multileaf collimator field segmentation

In intensity-modulated radiation therapy the aim is to realize given intensity distributions as a superposition of differently shaped fields. Multileaf collimators are used for field shaping. This segmentation task leads to discrete optimization problems, that are considered in this dissertation. A variety of algorithms for exact and approximated segmentation, for different objective functions and various technical as well as dosimetric constraints are developed

Algorithms for Geometric Facility Location: Centers in a Polygon and Dispersion on a Line

We study three geometric facility location problems in this thesis. First, we consider the dispersion problem in one dimension. We are given an ordered list of (possibly overlapping) intervals on a line. We wish to choose exactly one point from each interval such that their left to right ordering on the line matches the input order. The aim is to choose the points so that the distance between the closest pair of points is maximized, i.e., they must be socially distanced while respecting the order. We give a new linear-time algorithm for this problem that produces a lexicographically optimal solution. We also consider some generalizations of this problem. For the next two problems, the domain of interest is a simple polygon with n vertices. The second problem concerns the visibility center. The convention is to think of a polygon as the top view of a building (or art gallery) where the polygon boundary represents opaque walls. Two points in the domain are visible to each other if the line segment joining them does not intersect the polygon exterior. The distance to visibility from a source point to a target point is the minimum geodesic distance from the source to a point in the polygon visible to the target. The question is: Where should a single guard be located within the polygon to minimize the maximum distance to visibility? For m point sites in the polygon, we give an O((m + n) log (m + n)) time algorithm to determine their visibility center. Finally, we address the problem of locating the geodesic edge center of a simple polygon—a point in the polygon that minimizes the maximum geodesic distance to any edge. For a triangle, this point coincides with its incenter. The geodesic edge center is a generalization of the well-studied geodesic center (a point that minimizes the maximum distance to any vertex). Center problems are closely related to farthest Voronoi diagrams, which are well- studied for point sites in the plane, and less well-studied for line segment sites in the plane. When the domain is a polygon rather than the whole plane, only the case of point sites has been addressed—surprisingly, more general sites (with line segments being the simplest example) have been largely ignored. En route to our solution, we revisit, correct, and generalize (sometimes in a non-trivial manner) existing algorithms and structures tailored to work specifically for point sites. We give an optimal linear-time algorithm for finding the geodesic edge center of a simple polygon

Approximation Algorithms for NP-Hard Problems

The workshop was concerned with the most important recent developments in the area of efficient approximation algorithms for NP-hard optimization problems as well as with new techniques for proving intrinsic lower bounds for efficient approximation

Problems and applications of Discrete and Computational Geometry concerning graphs, polygons, and points in the plane

Esta tesistratasobreproblemasyaplicacionesdelageometríadiscretay computacional enelplano,relacionadosconpolígonos,conjuntosdepuntos y grafos. Después deunprimercapítulointroductorio,enelcapítulo 2 estudiamos una generalizacióndeunfamosoproblemadevisibilidadenelámbitodela O-convexidad. Dadounconjuntodeorientaciones(ángulos) O, decimosque una curvaes O-convexa si suintersecciónconcualquierrectaparalelaauna orientaciónde O es conexa.Cuando O = {0◦, 90◦}, nosencontramosenel caso delaortoconvexidad,consideradodeespecialrelevancia.El O-núcleo de unpolígonoeselconjuntodepuntosdelmismoquepuedenserconectados con cualquierotropuntodelpolígonomedianteunacurva O-convexa.En este trabajoobtenemos,para O = {0◦} y O = {0◦, 90◦}, unalgoritmopara calcular ymantenerel O-núcleodeunpolígonoconformeelconjuntode orientaciones O rota. Dichoalgoritmoproporciona,además,losángulosde rotación paralosqueel O-núcleotieneáreayperímetromáximos. En elcapítulo 3 consideramos unaversiónbicromáticadeunproblema combinatorioplanteadoporNeumann-LarayUrrutia.Enconcreto,de- mostramos quetodoconjuntode n puntosazulesy n puntosrojosenel plano contieneunparbicromáticodepuntostalquetodocírculoquelos tenga ensufronteracontieneensuinterioralmenos n(1− 1 √2 )−o(n) puntos del conjunto.Esteproblemaestáfuertementeligadoalcálculodelosdiagra- mas deVoronoideordensuperiordelconjuntodepuntos,pueslasaristas de estosdiagramascontienenprecisamentetodosloscentrosdeloscírculos que pasanpordospuntosdelconjunto.Porello,nuestralíneadetrabajo actual enesteproblemaconsisteenexplorarestaconexiónrealizandoun estudio detalladodelaspropiedadesdelosdiagramasdeVoronoideorden superior. En loscapítulos 4 y 5, planteamosdosaplicacionesdelateoríadegrafos 6 7 al análisissensorialyalcontroldeltráficoaéreo,respectivamente.Enel primer caso,presentamosunnuevométodoquecombinatécnicasestadísti- cas ygeométricasparaanalizarlasopinionesdelosconsumidores,recogidas a travésdemapeoproyectivo.Estemétodoesunavariacióndelmétodo SensoGraph ypretendecapturarlaesenciadelmapeoproyectivomediante el cálculodelasdistanciaseuclídeasentrelosparesdemuestrasysunor- malización enelintervalo [0, 1]. Acontinuación,aplicamoselmétodoaun ejemplo prácticoycomparamossusresultadosconlosobtenidosmediante métodosclásicosdeanálisissensorialsobreelmismoconjuntodedatos. En elsegundocaso,utilizamoslatécnicadelespectro-coloreadodegrafos para plantearunmodelodecontroldeltráficoaéreoquepretendeoptimizar el consumodecombustibledelosavionesalmismotiempoqueseevitan colisiones entreellos.This thesisdealswithproblemsandapplicationsofdiscreteandcomputa- tional geometryintheplane,concerningpolygons,pointsets,andgraphs. After afirstintroductorychapter,inChapter 2 westudyageneraliza- tion ofafamousvisibilityproblemintheframeworkof O-convexity. Given a setoforientations(angles) O, wesaythatacurveis O-convex if itsin- tersection withanylineparalleltoanorientationin O is connected.When O = {0◦, 90◦}, wefindourselvesinthecaseoforthoconvexity,consideredof specialrelevance.The O-kernel of apolygonisthesubsetofpointsofthe polygonthatcanbeconnectedtoanyotherpointofthepolygonwithan O-convexcurve.Inthisworkweobtain,for O = {0◦} and O = {0◦, 90◦}, an algorithm tocomputeandmaintainthe O-kernelofapolygonasthesetof orientations O rotates. Thisalgorithmalsoprovidestheanglesofrotation that maximizetheareaandperimeterofthe O-kernel. In Chapter 3, weconsiderabichromaticversionofacombinatorialprob- lem posedbyNeumann-LaraandUrrutia.Specifically,weprovethatevery set of n blue and n red pointsintheplanecontainsabichromaticpairof pointssuchthateverycirclehavingthemonitsboundarycontainsatleast n(1 − 1 √2 ) − o(n) pointsofthesetinitsinterior.Thisproblemisclosely related toobtainingthehigherorderVoronoidiagramsofthepointset.The edges ofthesediagramscontain,precisely,allthecentersofthecirclesthat pass throughtwopointsoftheset.Therefore,ourcurrentlineofresearch on thisproblemconsistsonexploringthisconnectionbystudyingindetail the propertiesofhigherorderVoronoidiagrams. In Chapters 4 and 5, weconsidertwoapplicationsofgraphtheoryto sensory analysisandairtrafficmanagement,respectively.Inthefirstcase, weintroduceanewmethodwhichcombinesgeometricandstatisticaltech- niques toanalyzeconsumeropinions,collectedthroughprojectivemapping. This methodisavariationofthemethodSensoGraph.Itaimstocapture 4 5 the essenceofprojectivemappingbycomputingtheEcuclideandistances betweenpairsofsamplesandnormalizingthemtotheinterval [0, 1]. Weap- ply themethodtoareal-lifescenarioandcompareitsperformancewiththe performanceofclassicmethodsofsensoryanalysisoverthesamedataset. In thesecondcase,weusetheSpectrumGraphColoringtechniquetopro- poseamodelforairtrafficmanagementthataimstooptimizetheamount of fuelusedbytheairplanes,whileavoidingcollisionsbetweenthem

Large bichromatic point sets admit empty monochromatic 4-gons

We consider a variation of a problem stated by Erd˝os 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 ≥ 5044 points in R2 in general position determines at least one empty, monochromatic quadrilateral (and thus linearly many).Postprint (published version