The 2x2 Simple Packing Problem André van Renssen Supervisor: Bettina Speckmann.

Slides:



Advertisements
Similar presentations
Weighted Matching-Algorithms, Hamiltonian Cycles and TSP
Advertisements

Approximation algorithms for geometric intersection graphs.
Chapter 4 Partition I. Covering and Dominating.
Minimum Clique Partition Problem with Constrained Weight for Interval Graphs Jianping Li Department of Mathematics Yunnan University Jointed by M.X. Chen.
Minimum Vertex Cover in Rectangle Graphs
Reducibility Class of problems A can be reduced to the class of problems B Take any instance of problem A Show how you can construct an instance of problem.
1 The TSP : Approximation and Hardness of Approximation All exact science is dominated by the idea of approximation. -- Bertrand Russell ( )
Complexity class NP Is the class of languages that can be verified by a polynomial-time algorithm. L = { x in {0,1}* | there exists a certificate y with.
CPE702 Complexity Classes Pruet Boonma Department of Computer Engineering Chiang Mai University Based on Material by Jenny Walter.
Approximation Algorithms Chapter 5: k-center. Overview n Main issue: Parametric pruning –Technique for approximation algorithms n 2-approx. algorithm.
CS774. Markov Random Field : Theory and Application Lecture 17 Kyomin Jung KAIST Nov
Piecewise Convex Contouring of Implicit Functions Tao Ju Scott Schaefer Joe Warren Computer Science Department Rice University.
On the complexity of orthogonal compaction maurizio patrignani univ. rome III.
PCPs and Inapproximability Introduction. My T. Thai 2 Why Approximation Algorithms  Problems that we cannot find an optimal solution.
Complexity 16-1 Complexity Andrei Bulatov Non-Approximability.
Minimum Vertex Cover in Rectangle Graphs R. Bar-Yehuda, D. Hermelin, and D. Rawitz 1.
WALCOM 2012February 16, 2012 Stephane Durocher Debajyoti Mondal Department of Computer Science University of Manitoba.
Vertex Cover, Dominating set, Clique, Independent set
The Theory of NP-Completeness
Tetra-Cubes: An algorithm to generate 3D isosurfaces based upon tetrahedra BERNARDO PIQUET CARNEIRO CLAUDIO T. SILVA ARIE E. KAUFMAN Department of Computer.
UMass Lowell Computer Science Analysis of Algorithms Prof. Karen Daniels Spring, 2006 Lecture 7 Monday, 4/3/06 Approximation Algorithms.
CSE 326: Data Structures NP Completeness Ben Lerner Summer 2007.
Computing the Banzhaf Power Index in Network Flow Games
Analysis of Algorithms CS 477/677
NP-complete examples CSC3130 Tutorial 11 Xiao Linfu Department of Computer Science & Engineering Fall 2009.
On Stochastic Minimum Spanning Trees Kedar Dhamdhere Computer Science Department Joint work with: Mohit Singh, R. Ravi (IPCO 05)
Chapter 4: Straight Line Drawing Ronald Kieft. Contents Introduction Algorithm 1: Shift Method Algorithm 2: Realizer Method Other parts of chapter 4 Questions?
Vertex cover problem S  V such that for every {u,v}  E u  S or v  S (or both)
1 University of Denver Department of Mathematics Department of Computer Science.
The Art Gallery Problem
The Art Gallery Problem
Part I: Introductory Materials Introduction to Graph Theory Dr. Nagiza F. Samatova Department of Computer Science North Carolina State University and Computer.
Introduction to Routing. The Routing Problem Apply after placement Input: –Netlist –Timing budget for, typically, critical nets –Locations of blocks and.
Visibility Graphs and Cell Decomposition By David Johnson.
A brief and sketchy intro to 3D Convex Hulls Rodrigo Silveira GEOC 2010/11 - Q2.
1 Introduction to Approximation Algorithms. 2 NP-completeness Do your best then.
1 The TSP : NP-Completeness Approximation and Hardness of Approximation All exact science is dominated by the idea of approximation. -- Bertrand Russell.
1 Introduction to Approximation Algorithms. 2 NP-completeness Do your best then.
Advanced Algorithm Design and Analysis (Lecture 13) SW5 fall 2004 Simonas Šaltenis E1-215b
Tonga Institute of Higher Education Design and Analysis of Algorithms IT 254 Lecture 8: Complexity Theory.
Approximation Algorithms
Week 10Complexity of Algorithms1 Hard Computational Problems Some computational problems are hard Despite a numerous attempts we do not know any efficient.
Nonoverlap of the Star Unfolding Boris Aronov and Joseph O’Rourke, 1991 A Summary by Brendan Lucier, 2004.
Combinatorial Optimization Problems in Computational Biology Ion Mandoiu CSE Department.
Techniques for Proving NP-Completeness Show that a special case of the problem you are interested in is NP- complete. For example: The problem of finding.
Optimal Rectangular Partition of a Rectilinear Polygonal Region
1 Chapter 34: NP-Completeness. 2 About this Tutorial What is NP ? How to check if a problem is in NP ? Cook-Levin Theorem Showing one of the most difficult.
NP-COMPLETE PROBLEMS. Admin  Two more assignments…  No office hours on tomorrow.
NP-Complete problems.
1 CS612 Algorithms for Electronic Design Automation CS 612 – Lecture 8 Lecture 8 Network Flow Based Modeling Mustafa Ozdal Computer Engineering Department,
Chapter 4 Partition (1) Shifting Ding-Zhu Du. Disk Covering Given a set of n points in the Euclidean plane, find the minimum number of unit disks to cover.
CPS Computational problems, algorithms, runtime, hardness (a ridiculously brief introduction to theoretical computer science) Vincent Conitzer.
CS6045: Advanced Algorithms NP Completeness. NP-Completeness Some problems are intractable: as they grow large, we are unable to solve them in reasonable.
Algorithms for hard problems Introduction Juris Viksna, 2015.
NP Completeness Piyush Kumar. Today Reductions Proving Lower Bounds revisited Decision and Optimization Problems SAT and 3-SAT P Vs NP Dealing with NP-Complete.
Introduction to NP-Completeness Tahir Azim. The Downside of Computers Many problems can be solved in linear time or polynomial time But there are also.
Computational Complexity Shirley Moore CS4390/5390 Fall 2013 August 27, 2013.
Graphs Definition: a graph is an abstract representation of a set of objects where some pairs of the objects are connected by links. The interconnected.
Given this 3-SAT problem: (x1 or x2 or x3) AND (¬x1 or ¬x2 or ¬x2) AND (¬x3 or ¬x1 or x2) 1. Draw the graph that you would use if you want to solve this.
The geometric GMST problem with grid clustering Presented by 楊劭文, 游岳齊, 吳郁君, 林信仲, 萬高維 Department of Computer Science and Information Engineering, National.
Chapter 5 Guillotine Cut (1) Rectangular Partition Ding-Zhu Du.
COSC 3101A - Design and Analysis of Algorithms 14 NP-Completeness.
The NP class. NP-completeness Lecture2. The NP-class The NP class is a class that contains all the problems that can be decided by a Non-Deterministic.
Hongyu Liang Institute for Theoretical Computer Science Tsinghua University, Beijing, China The Algorithmic Complexity.
34.NP Completeness. Computer Theory Lab. Chapter 34P.2.
Construction We constructed the following graph: This graph has several nice properties: Diameter Two Graph Pebbling Tim Lewis 1, Dan Simpson 1, Sam Taggart.
TU/e Algorithms (2IL15) – Lecture 11 1 Approximation Algorithms.
Minimum-Segment Convex Drawings of 3-Connected Cubic Plane Graphs
Computability and Complexity
Haitao Wang Utah State University SoCG 2017, Brisbane, Australia
Presentation transcript:

The 2x2 Simple Packing Problem André van Renssen Supervisor: Bettina Speckmann

/ Department of Mathematics and Computer Science Introduction Input: An axis-aligned polygon P drawn on a grid. P consists of n edges and contains N cells. Question: How many non-overlapping 2x2 squares can be packed into P?

/ Department of Mathematics and Computer Science State of the art NP-Complete for polygons with holes (Berman et al. 1981, Dulieu et al. 2009) Unknown for simple polygons PTAS (in N) for simple polygons and polygons with holes (Chan, 2004) Some special cases solvable in polynomial time (in n) (El-Khechen, 2009)

/ Department of Mathematics and Computer Science A simple technique

/ Department of Mathematics and Computer Science More ideas Maximizing the number of squares on boundary does not work Restricting to rectilinear convex does not help

/ Department of Mathematics and Computer Science Different approach Instead of looking at where to place squares, look at where NOT to place squares Needs some way to keep track of usable locations This leads to a graph representation

/ Department of Mathematics and Computer Science Graph V: vertex for each possible location of a square E: edge between vertex u and v iff their squares overlap O(n log n + |V|) construction time |V| is proportional to OPT

Reduction / Department of Mathematics and Computer Science

Reduction / Department of Mathematics and Computer Science

Additional reduction rules Cycles (with and without connections)

/ Department of Mathematics and Computer Science Additional reduction rules

Cornered diamonds / Department of Mathematics and Computer Science Additional reduction rules

/ Department of Mathematics and Computer Science Construction scheme

Polygons revisited For some configurations of edges: Always same number of squares Always same part of polygon removed / Department of Mathematics and Computer Science

Polygons revisited Algorithm: While the polygon is not solved: −Find a configuration −Remove the configuration Finding a configuration: O(n) time Removing a configuration: O(1) time Every configuration removes some edge(s): at most O(n) times Total running time: O(n 2 ) / Department of Mathematics and Computer Science

Polygons revisited / Department of Mathematics and Computer Science

Not (yet) solvable / Department of Mathematics and Computer Science

Conclusion Reduction rules: Runs in time polynomial in |V| Configuration removal: Runs in O(n 2 ) time Not shown during presentation: An O(n log n)-time algorithm for polygons having only even length vertical edges Improved running time of the ½-approximation algorithm (Berman et al. 1982) from O(N) to O(n 2 ) All graph reduction techniques are implemented / Department of Mathematics and Computer Science

Open problems Is this problem NP-hard? Find better approximations or PTAS in n Solve class of rectilinear convex polygons Prove (if possible) that |V| is polynomial in n after modifying the polygon / Department of Mathematics and Computer Science