Generalized kernels of polygons under rotation

Given a set $\mathcal{O}$ of $k$ orientations in the plane, two points inside a simple polygon $P$ $\mathcal{O}$-see each other if there is an $\mathcal{O}$-staircase contained in $P$ that connects them. The $\mathcal{O}$-kernel of $P$ is the subset of points which $\mathcal{O}$-see all the other points in $P$. This work initiates the study of the computation and maintenance of the $\mathcal{O}$-${\rm Kernel}$ of a polygon $P$ as we rotate the set $\mathcal{O}$ by an angle $\theta$, denoted $\mathcal{O}$-${\rm Kernel}_{\theta}(P)$. In particular, we design efficient algorithms for (i) computing and maintaining $\{0^{o}\}$-${\rm Kernel}_{\theta}(P)$ while $\theta$ varies in $[-\frac{\pi}{2},\frac{\pi}{2})$, obtaining the angular intervals where the $\{0^{o}\}$-${\rm Kernel}_{\theta}(P)$ is not empty and (ii) for orthogonal polygons $P$, computing the orientation $\theta\in[0, \frac{\pi}{2})$ such that the area and/or the perimeter of the $\{0^{o},90^{o}\}$-${\rm Kernel}_{\theta}(P)$ are maximum or minimum. These results extend previous works by Gewali, Palios, Rawlins, Schuierer, and Wood.Comment: 12 pages, 4 figures, a version omitting some proofs appeared at the 34th European Workshop on Computational Geometry (EuroCG 2018

Approximation Algorithms for Illuminating 1.5D Terrain

We review important algorithmic results for the coverage of 1.5D terrain by point guards. Finding the minimum number of point guards for covering 1.5D terrain is known to be NP-hard. We propose two approximation algorithms for covering 1.5D terrain by a fewer number of point guards. The first algorithm (Greedy Ranking Algorithm) is based on ranking vertices in term of number of visible edges from them. The second algorithm (Greedy Forward Marching Algorithm) works in greedy manner by scanning the terrain from left to right. Both algorithms are implemented in Python 2.7 programming language

Generating Kernel Aware Polygons

Problems dealing with the generation of random polygons has important applications for evaluating the performance of algorithms on polygonal domain. We review existing algorithms for generating random polygons. We present an algorithm for generating polygons admitting visibility properties. In particular, we propose an algorithm for generating polygons admitting large size kernels. We also present experimental results on generating such polygons

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