ISA'91 Algorithms: 2nd International Symposium on Algorithms Taipei, Republic of China, December 16–18, 1991 Proceedings

406 Pages·1991·6.556 MB·English

by  Christos H. Papadimitriou (auth.), Wen-Lian Hsu, R. C. T. Lee (eds.)

Lecture Notes in Computer Science 557
Edited by G. Goos and J. Hartmanis
Advisory Board: W. Brauer D. Gries J. Stoer
.W L. Hsu R.C.T. Lee ~.s~(
ISA '91 Algorithms
2nd International Symposium on Algorithms
Taipei, Republic of China, December 16-18, 1991
Proceedings
galreV-regnirpS
Berlin Heidelberg NewYork
London Pads Tokyo
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Series Editors
Gerhard Goos Jufis Hartmanis
Universit~it Karlsruhe Department of Computer Science
Postfach 69 80 Cornell University
Vincenz-Priessnitz-Stral3e 1 5148 Upson Hall
W-7500 Karlsruhe, FRG Ithaca, NY 14853, USA
Volume Editors
Wen-Lian Hsu
Institute of Information Science, Academia Sinica
Nankang, Taipei, Taiwan 115, Republic of China
R. C. T. Lee
Institute of Computer Science, Tsing Hua University
Hsin Chu, Republic of China
CR Subject Classification (1991): E1-2, G.2-3, 1.1.2, 1.3.5
ISBN 3-540-54945-5 Springer-Verlag Berlin Heidelberg New York
ISBN 0-387-54945-5 Springer-Verlag New York Berlin Heidelberg
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Preface
The papers in this volume were presented at the Second Annual International Symposium on
Algorithms. The conference took place December 61 L ,81 1991, at Academia Sinica in Taipei,
Taiwan, Republic of China. It was organized by the Institute of Information Science, Academia
Sinica and the National Tsing Hua University, in cooperation with the Special Interest Group on
Algorithms (SIGAL) of the Information Processing Society of Japan (IPSJ) and the Technical
Group on Theoretical Foundation of Computing of the Institute of Electronics, Information and
Communication Engineers 0EICE).
The goal of the annual International Symposium on Algorithms (ISA) is to provide a forum for
researchers in the Pacific rim as well as other parts of the world to exchange ideas on computing
theory. The first such symposium was held 1990 in Tokyo, Japan as "SIGAL International
Symposium on Algorithms".
In response to the program committee's call for papers, 90 papers were submitted. From these
submissions, the committee selected 63 for presentation at the symposium. In addition to these
contributed papers, the symposium included 5 invited presentations.
~w.ember 1991 Wen-Lian Hsu
R. C. T. Lee
Symposium Chairs: Finance:
R. .C T. Lee (Tsing Hua Univ.) Ting-Yi Sung (Academia )aciniS
Wen-Lian Hsu (Academia )aciniS
Local Arrangement:
Program Committee: R. .C Chang (Chiao Tung Univ.)
Takao Asano (Sophia Univ.) Ming-Tat Ko (Academia Sinica)
Tetsuo Asano (Osaka Electro-Comm. Univ.)
Francis .Y L. Chin (Univ. of Hong Kong) Publication, Publicity:
Wen-Lian Hsu (Academia )aciniS Jan-Ming Ho (Academia Sinica)
Toshihide Ibaraki (Kyoto Univ.)
Hiroshi Imai (Univ. of Tokyo)
Supported by
D. T. Lee (Northwestern Univ.)
National Science Council of ROC
Sing-Ling Lee (Chung Cheng Univ.)
Institute for Information Industry
C. L. Liu (Univ. of Illinois)
Telecommunication Laboratories
Kurt Mehlhorn (Univ. Saarland)
Takao Nishizeki (Tohoku Univ.)
Jia-Shung Wang (Tsing Hua Univ.)
Contents
Session 1: Invited Presentation
Decision-Making with Incomplete Information ................................ 1
C. H. Papadimitriou (Univ. of California)
Session 2A
Maximum Independent Set of a Permutation Graph in k Tracks ..................... 2
D. T. Lee, Majid Sarrafzadeh (Northwestern Univ.)
Algorithms for Square Roots of Graphs ................................... 12
Yaw-Ling Lin, Steven S. Skiena (State Univ. of New York, Stony Brook)
Session 2B
Distributed k-Mutual Exclusion Problem and k-Coteries ......................... 22
Satoshi Fujita, Masafumi Yamashita, Tadashi Ae (Hiroshima Univ.)
Is the Shuffle-Exchange Better Than the Butterfly? ............................ 32
Arvind Raghunathan (Univ. of California, Davis), Huzur Saran (Indian Institute
of Technology)
Session 3: Invited Presentation
Weighted Random Assignments with Application to Hashing ..................... 42
A. C. Yao (Princeton Univ.)
Session 4A
Scheduling File Transfers under Port and Channel Constraints .................... 43
Shin-Ichi Nakano, Takao Nishizeki (Tohoku Univ.)
Substitution Decomposition on Chordal Graphs and Applications .................. 52
Wen-Lian Hsu, Tze-Heng Ma (Institute of Information Science, Academia
Sinica)
Mixed-Searching and Proper-Path-Width .................................. 61
Atsushi Takahashi, Shuichi Ueno, Yoji Kajitani (Tokyo Institute of Technology)
Session 4B
Short Wire Routing in Convex Grids ..................................... 72
Frank Wagner, Barbara Wolfers (Institut for Informatik, Freie Univ. Berlin)
A New Approach to Knock-Knee Channel Routing ........................... 83
Dorothea Wagner (Technische Univ. Berlin)
Circuit Partitioning Algorithms: Graph Model versus Geometry Model .............. 94
Tetsuo Asano (Osaka Electro-Communication Univ.), Takeshi Tokuyama (IBM
Research, Tokyo Research Laboratory)
IIIV
Session 5A
Identifying 2-Monotonic Positive Boolean Functions in Polynomial Time ............ 104
Endre Boros, Peter L. Hammer (Rutgers Univ., Bush Campus),
Toshihide Ibaraki, Kazuhiko Kawakami (Kyoto Univ.)
An Average Case Analysis of Monien and Speckenmeyer's Mechanical Theorem
Proving Algorithm ................................................. 611
T. H. Hu, C. .Y Tang, .R C. T. Lee (Tsing Hua Univ.)
Session 5B
An On-Line Algorithm for Navigating in Unknown Terrain ..................... 721
Kwong-Fai Chan, Tak Wah Lam (Univ. of Hong Kong)
On Maintaining the Width and Diameter of a Planar Point-Set Online ............... 731
Ravi Janardan (Univ. of Minnesota)
Session 6: Invited Presentation
Optimal Triangulations by Retriangulating ................................. 051
Herbert Edelsbrunner (Univ. of Illinois)
Session 7A
Approximating Polygons and Subdivisions with Minimum Link Paths .............. 151
Leonidas J. Guibas, John E. Hershberger (DEC System Research Center, Palo
Alto, CA), Joseph .S .B Mitchell (SORIE, Cornell Univ.), Jack Scott Snoeyink
(Utrecht Univ.)
An Incremental Algorithm for Constructing Shortest Watchman Routes ............. 361
Xue-Hou Tan, Tomio Hirata, Yasuyoshi Inagaki (Nagoya Univ.)
On Hitting Grid Points in a Convex Polygon with Straight Lines .................. 671
H. .S Lee, R. .C Chang (Chiao Tung Univ.)
Session 7B
On the Complexity of Some Hamiltonian and Eulerian Problems in Edge-Colored
Complete Graphs ................................................. 091
A. Benkouar (Univ. Paris-Xll), .Y G. Manoussakis (LRI, Univ. de Pads-Sud),
V.Th. Paschos (CERMSEM, Univ. de Paris, I-Sorbonne-Pantheon), and R. Saad
(LRI, Univ. de Paris-Sud)
Dynamic Programming on Intervals ..................................... 991
Takao Asano (Sophia Univ.)
Combinatorial Optimization Through Order Statistics ......................... 802
Wojciech Szpankowski (Purdue Univ.)
Session 8: Invited Presentation
Combinatorics and Algorithms of Geometric Arrangements ..................... 218
Leonidas J. Guibas (Stanford Univ. and DEC System Research Center)
XI
Session 9A
An Analysis of Randomized Shear Sort on the Mesh Computer .................. 219
Susumu Hasegawa, Hiroshi Imai, Koji Hakata (Univ. of Tokyo)
Efficient Parallel Divide-and-Conquer for a Class of lnterconnection Topologies ....... 229
I-Chen Wu (Carnegie Mellon Univ.)
Optimal Specified Root Embedding of Full Binary Trees in Faulty Hypercubes ....... 241
M. Y. Chan, F. Y. L. Chin, C. K. Poon (Univ. of Hong Kong)
Session 9B
A Tight Lower Bound for the Worst Case of Bottom-Up Heapsort ................ 251
Rudolf Fleischer (Univ. of Saarland)
Historical Searching and Sorting ....................................... 263
Alistair Moffat (Univ. of Melbourne), Ola Petersson (Lund Univ.)
Comparison-Efficient and Write-Optimal Searching and Sorting .................. 273
Arne Andersson (Lund Univ.), Tony W. Lai (NIT Basic Research
Laboratories)
Session 10: Invited Presentation
Nearest Neighbors Revisited .......................................... 283
F. Yao (Xerox Palo Alto Research Center)
Session llA
Competitiveness and Response Time in On-Line Algorithms ..................... 284
Vladimir Estivill-Castro (York Univ.), Murray Sherk (Univ. of Waterloo)
A Linear Time Optimal Via Assignment Algorithm for Three-Dimensional Channel
Routing ........................................................ 294
Jan-Ming Ho (Institute of Information Sciences, Academia Sinica)
Symmetry of Information and One-Way Functions ........................... 308
Luc Longpr6 (Northeastern Univ.), Sarah Mocas (Northeastern Univ.)
Session lIB
A Linear Time Algorithm to Recognize the Double Euler Trail for Series-Parallel
Networks ....................................................... 3 16
Lih-Hsing Hsu, J. Y. Hwang, T. Y. Ho, C. H. Tsai (Chiao Tung Univ.)
On Finding a Smallest Augmentation to Biconnect a Graph ...................... 326
Tsan-Sheng Hsu, Vijaya Ramachandran (Univ. of Texas at Austin)
A Faster Algorithm for Edge-Disjoint Paths in Planar Graphs .................... 336
Michael Kaufmann, Gerhard KI~ (Max-Planck-institut rit'f Informatik, Saarbriicken)
Session 12A
An Optimal Construction Method for Generalized Convex Layers ................. 349
Hans-Peter Lenhof, Michiel Smid (Max-Planck-Institut rit'f Informatik, Saarbriicken)
Rectangular Point Location and the Dynamic Closest Pair Problem ................. 364
Michiel Smid (Max-Planck-Institut fiir Informatik, Saarbrticken)
Session 12B
Parallel Algorithms for Some Dominance Problems Based on a CREW PRAM ........ 375
Ip-Wang Chan (National Univ. of Singapore), Donald K. Friesen (Texas
A&M Univ.)
Parallel Algorithms for Finding Maximal k-Dependent Sets and Maximal f-Matchings .... 385
Krzysztof Diks (Institute of Informatics, Warsaw Univ.), Oscar Garrido,
Andrzej Lingas (Lund Univ.)
Author Index .................................................... 396
DECISION-MAKING WITH INCOMPLETE INFORMATION
Christos H. Papadimitriou
University of California at San Diego
ABSTRACT
We must often make decisions in situations such as routing, scheduling,
compiling, and resource allocation, without crucial information about (respec-
tively) the terrain topography, the execution times, the run-time environment,
and the future requests. Information may be unavailable because of its tem-
poral or distributed nature. A reasonable way to assess the effectiveness of a
decision rule in such situations is to compare its outcome to the ideal opti-
mum solution, attainable only if we had complete information. An algorithm
is considered effective (or "competitive") if its performance is a multiplicative
constant away from the ideal solution. We review some recent and on-going
work on this active area.
Maximum Independet Set of a Permutation Graph
in k Tracks 1
D. T. Lee and Majid Sarrafzadeh
Department of Electrical Engineering
and Computer Science
Northwestern University
Evanston, IL 60208
Abstract
A maximum independent set of a permutation graph is a maximum subset of noncross-
ing chords in a matching diagram 4. (~ consists of a set of chords with end-points on two
horizontal lines.) The problem of finding, among all noncrossing subsets of ~ with density
at most k, one with maximum size is considered, where the density of a subset is the max-
imum number of chords crossing a vertical line and k is a given parameter. A O(n log n)
time and O(n) space algorithm, for solving the problem with n chords, is proposed. Ks
an application, we solve the problem of finding, among all proper subsets with density at
most k of an interval graph, one with maximum number of intervals.
1 Introduction
Consider two rows of distinct integer points in the xy-plane. The lower row is at y = bl and
the upper row at y = b2, for some bl < b2. A chord Ni = (s is a line segment passing
through points (s bl) and (ui, )2b of the plane where s is the lower terminal and ui is the
upper terminal of Ni. A matching diagram consists of a collection 4 = { N1,..., Nn) of chords.
A subset of 4 is called an independent set if the corresponding chords are pairwise noncrossing.
An independent set of maximum cardinality, among all independent sets, is called a maximum
independent set (MIS). The density d a of a subset 4~ of 4 at a half-integer column x = i + (cid:1)89
(where i is an integer) is defined as follows.
d~= {N=(g,u) e4als189 or u<i-{-(cid:1)89163
The density ~d of a subset 4~ of 4 is maxi(d~), for all i.
Throughout siht paper, we assume the input si a noitcelloC of (unsorted) pairs ,il( .)iu A
geometric algorithm rof obtaining a maximum independent tes of 4 ni O(nlogn) time has
been obtained, where n = 141 AK. However the density of the gnitluser MIS can be sa egral
sa .n MIS-k problem si to ,dnif among lla independent subsets of 4 with density ta most ,k
one with maximum ytilauidrac (Figure .)1 Note that MIS-n si the lanoitidart MIS problem
and MIS-1 problem si that of gnidnif a maximum independent tes of a noitcelloc of slavretni
aSupported in part by the National Science Foundation under grants 5181098-RCC and .0451298-PIM