Jekyll2018-12-04T14:53:32+00:00https://pacechallenge.org/feed.xmlPACEParameterized Algorithms and Computational ExperimentsPACE ChallengePACE 2018 ceremony at IPEC2018-08-27T00:00:00+00:002018-08-27T00:00:00+00:00https://pacechallenge.org/2018/08/27/PACE-2018-ceremony-at-IPEC<p>The award ceremony took place in Helsinki. The <a href="https://bit.ly/PACE2018-talk">slides</a> are available and show the results.</p>
<p>Some pictures (courtesy of Tom van der Zanden):</p>
<p><img src="https://pacechallenge.files.wordpress.com/2018/08/a.jpg" alt="" /></p>
<p><img src="https://pacechallenge.files.wordpress.com/2018/08/b.jpg" alt="" /></p>
<p><img src="https://pacechallenge.files.wordpress.com/2018/08/c.jpg" alt="" /></p>
<p><img src="https://pacechallenge.files.wordpress.com/2018/08/d.jpg" alt="" /></p>
<p><img src="https://pacechallenge.files.wordpress.com/2018/08/e.jpg" alt="" /></p>
<p>Thanks to all participants!</p>PACE ChallengeThe award ceremony took place in Helsinki. The slides are available and show the results.PACE 2018 now on OPTIL.io2017-12-12T00:00:00+00:002017-12-12T00:00:00+00:00https://pacechallenge.org/2017/12/12/PACE-2018-now-on-optil.io<p>We are happy to announce that PACE 2018 will cooperate again with
<a href="http://optil.io">OPTIL.io</a> to handle the submission process and the
evaluation of the submissions. <a href="http://optil.io">OPTIL.io</a> is a website
for organizing programming challenges on optimization problems, created
and maintained by the <a href="http://www2.cs.put.poznan.pl/">Institute of Computing
Science</a> of <a href="https://www.put.poznan.pl/">Poznan University of
Technology</a>.</p>
<p>For all the tracks, the participants have the possibility to submit
their code and run it on the 100 public test instances. Due to the
workload, submissions are allowed only once every 24 hours.
There is also a lite version of the public instances in
which the program can be tested on fewer instances and with a shorter
timeout of 5 minutes.</p>
<p>Here are the links for submitting your programs:</p>
<ul>
<li>Track A: <a href="https://www.optil.io/optilion/problem/3023">https://www.optil.io/optilion/problem/3023</a></li>
<li>
<p>Track A lite: <a href="https://www.optil.io/optilion/problem/3026">https://www.optil.io/optilion/problem/3026</a></p>
</li>
<li>Track B: <a href="https://www.optil.io/optilion/problem/3024">https://www.optil.io/optilion/problem/3024</a></li>
<li>
<p>Track B lite: <a href="https://www.optil.io/optilion/problem/3027">https://www.optil.io/optilion/problem/3027</a></p>
</li>
<li>Track C: <a href="https://www.optil.io/optilion/problem/3025">https://www.optil.io/optilion/problem/3025</a></li>
<li>Track C lite: <a href="https://www.optil.io/optilion/problem/3028">https://www.optil.io/optilion/problem/3028</a></li>
</ul>
<p>If you have any trouble submitting your code, please contact us or the
organizers of Optil.io.</p>
<p>Good luck!</p>PACE ChallengeWe are happy to announce that PACE 2018 will cooperate again with OPTIL.io to handle the submission process and the evaluation of the submissions. OPTIL.io is a website for organizing programming challenges on optimization problems, created and maintained by the Institute of Computing Science of Poznan University of Technology.PACE 2018 Call for Participation2017-11-14T00:00:00+00:002017-11-14T00:00:00+00:00https://pacechallenge.org/2017/11/14/PACE-2018-Call-for-Participation<p>The PACE 2018 challenge has started! This year there is only one problem, Steiner Tree, and three tracks: two for exact algorithms and one for heuristics. To register your team now and find out all the details of the challenge, visit the <a href="/2018/steiner-tree">challenge page</a>.</p>PACE ChallengeThe PACE 2018 challenge has started! This year there is only one problem, Steiner Tree, and three tracks: two for exact algorithms and one for heuristics. To register your team now and find out all the details of the challenge, visit the challenge page.Extension of submission deadline2017-04-28T00:00:00+00:002017-04-28T00:00:00+00:00https://pacechallenge.org/2017/04/28/Extension-of-submission-deadline<p>Due to numerous requests, we decided to allow submissions for Track A and Track B until May 25. Thanks to the cooperation with <a href="https://optil.io">OPTIL.io</a>, we can still send out the notification on June 1.</p>
<p>We wish all of the participants good luck and fun in the remaining weeks.</p>PACE ChallengeDue to numerous requests, we decided to allow submissions for Track A and Track B until May 25. Thanks to the cooperation with OPTIL.io, we can still send out the notification on June 1.PACE is cooperating with OPTIL.io2017-03-07T00:00:00+00:002017-03-07T00:00:00+00:00https://pacechallenge.org/2017/03/07/PACE-cooperation-optil.io<p>March 1 has passed which means that submission is possible from now until May 1 for both tracks of PACE 2017.</p>
<p>We are happy to announce that PACE 2017 will cooperate with <a href="http://optil.io">OPTIL.io</a> to handle the submission process and the evaluation of submissions. <a href="http://optil.io">OPTIL.io</a> is a website for organizing programming challenges for optimization problems, created and maintained by the <a href="http://www2.cs.put.poznan.pl/">Institute of Computing Science</a> of <a href="https://www.put.poznan.pl/">Poznan University of Technology</a>.</p>
<h2 id="track-a">Track A</h2>
<p>For Track A, participants have the possibility to submit their code and run it on the 100 public test instances. Due to the workload, submissions are allowed only once every 48 hours. To test the compatibility of your software with the platform, there is also an unlimited ‘lite’ version of the test in which the program can be tested on fewer instances and with a timeout of 30 seconds. The leaderboard at <a href="http://optil.io">OPTIL.io</a> is independent of the official PACE Track A competition – the evaluation of the final submissions on the hidden instances will happen on the platform that is described on the Track A website.</p>
<ul>
<li><a href="https://www.optil.io/optilion/problem/3008">Track A1</a></li>
<li><a href="https://www.optil.io/optilion/problem/3004">Track A2</a></li>
<li><a href="https://www.optil.io/optilion/problem/3006">Track A lite</a></li>
</ul>
<h2 id="track-b">Track B</h2>
<p>For Track B, participants have the possibility to submit their code and run it on the 100 public test instances and also on the 100 hidden instances which are used for the final evaluation of the challenge. Due to the workload, submissions are allowed only once every 48 hours. As for Track A, there is also an unlimited ‘lite’ version of the test for the public instances in which the program can be tested on fewer instances and with a timeout of 30 seconds. For the hidden instances, we will announce a current leaderboard on this website. This leaderboard will show the current standing according to the competition rules of Track B, the leaderboard at <a href="http://optil.io">OPTIL.io</a> is independent.</p>
<ul>
<li><a href="https://www.optil.io/optilion/problem/3009">Track B, public and hidden instances</a></li>
<li><a href="https://www.optil.io/optilion/problem/3010">Track B, lite version with some public instances</a></li>
</ul>PACE ChallengeMarch 1 has passed which means that submission is possible from now until May 1 for both tracks of PACE 2017.PACE 2017 Announcement2016-12-01T00:00:00+00:002016-12-01T00:00:00+00:00https://pacechallenge.org/2016/12/01/PACE-2017-announcement<p>We are happy to announce the second iteration of PACE, the Parameterized Algorithms and Computational Experiments Challenge. The goal of PACE is to investigate the applicability of algorithmic ideas studied and developed in the subfields of multivariate, fine-grained, parameterized, or fixed-parameter tractable algorithms. The challenge consists of two separate tracks.</p>
<h2 id="track-a-treewidth-challenges">Track A (Treewidth Challenges)</h2>
<p>1) Compute a tree-decomposition of minimum width. You have 30 minutes per instance. Win by solving more instances than the other participants.</p>
<p>2) Compute some tree-decomposition. You have 30 minutes per instance. Win by printing solutions of smaller width than the other participants.</p>
<p>Detailed instructions and fresh instance sets: <a href="https://pacechallenge.wordpress.com/pace-2017/track-a-treewidth/">https://pacechallenge.wordpress.com/pace-2017/track-a-treewidth/</a></p>
<h2 id="track-b-minimum-fill-in-challenge">Track B (Minimum Fill-In Challenge)</h2>
<p>Given an undirected graph G, compute a smallest set of edges E such that adding E to G results in a chordal graph. You have 30 minutes per instance. Win by solving more instances than the other participants.</p>
<p>Detailed instructions and an instance set: <a href="https://pacechallenge.wordpress.com/pace-2017/track-b-minimum-fill-in/">https://pacechallenge.wordpress.com/pace-2017/track-b-minimum-fill-in/</a></p>
<h2 id="timeline">Timeline</h2>
<p>December 1st, 2016: Announcement of the challenges
March 1st, 2017: Submission of preliminary version for bugfixing and leaderboard
May 1st, 2017: Submission of final version
June 1st, 2017: Announcement of the results
September 4-8, 2017: Award ceremony at the International Symposium on Parameterized and Exact Computation (IPEC 2017) in Vienna</p>
<h2 id="program-committee">Program Committee</h2>
<p>Track A (tree width):</p>
<ul>
<li>Holger Dell (Saarland University and Cluster of Excellence (MMCI))</li>
</ul>
<p>Track B (min fill-in):</p>
<ul>
<li>Christian Komusiewicz (chair) (Friedrich-Schiller-University Jena)</li>
<li>Nimrod Talmon (Weizmann Institute of Science)</li>
<li>Mathias Weller (Laboratory of Informatics, Robotics, and Microelectronics of Montpellier (LIRMM))</li>
</ul>
<h2 id="steering-committee">Steering Committee</h2>
<ul>
<li>Holger Dell (Saarland University and Cluster of Excellence, MMCI)</li>
<li>Bart M. P. Jansen (Eindhoven University of Technology)</li>
<li>Thore Husfeldt (ITU Copenhagen and Lund University)</li>
<li>Petteri Kaski (Aalto University)</li>
<li>Christian Komusiewicz (Friedrich-Schiller-University Jena)</li>
<li>Frances A. Rosamond (chair) (Frances.Rosamond@uib.no, University of Bergen)</li>
</ul>PACE ChallengeWe are happy to announce the second iteration of PACE, the Parameterized Algorithms and Computational Experiments Challenge. The goal of PACE is to investigate the applicability of algorithmic ideas studied and developed in the subfields of multivariate, fine-grained, parameterized, or fixed-parameter tractable algorithms. The challenge consists of two separate tracks.Results of the First PACE Challenge2016-09-12T00:00:00+00:002016-09-12T00:00:00+00:00https://pacechallenge.org/2016/09/12/results-PACE-2016<p>The winners of the 1st PACE competition were presented at <a href="http://conferences.au.dk/algo16/algo-frontpage/">ALGO
2016</a> in Aarhus. For
those that couldn’t make it to Aarhus: here are the results. We would
like to thank all participants for making this 1st edition of PACE an
enjoyable and successful one.</p>
<h2 id="track-a-treewidth">Track A: Treewidth</h2>
<p>The <em>treewidth</em> of a graph is an important graph parameter, the theory
and complexity of which has been intensely study in graph minor theory
and fixed-parameter tractability (FPT). Given a graph G and an integer
k, it is NP-complete to determine whether the treewidth of G is at most
k, but there is an n^(k+2)-time algorithm (Arnborg, Corneil, and
Proskurowski 1987). The problem can also be solved in FPT-time exp(k^3)
n (Bodlaender 1996), and a factor-5 approximation can be obtained in
time exp(k) n (Bodlaender, Drange, Dregi, Fomin, Lokshtanov, and
Pilipczuk 2013). It is unknown whether the problem has a polynomial-time
approximation scheme (PTAS).</p>
<p>Treewidth implementations are used in various contexts. For example,
compilers allocate registers by computing proper colorings on control
flow graphs, which turn out to have small treewidth in practice (e.g.,
Thorup 1998). Data structures for shortest path queries can use tree
decompositions in a preprocessing phase (e.g., Chatterjee, Ibsen-Jensen,
and Pavlogiannis 2016). Graph theory can be guided by treewidth
implementations when attempting to rigorously determine the treewidth of
specific graph families (e.g., Kiyomi, Okamoto, and Otachi 2015).
Finally, many problems in probabilistic inference use tree
decompositions in a preprocessing phase (e.g., Otten, Ihler, Kask, and
Dechter 2011).</p>
<p>While some treewidth implementations existed before PACE 2016, they were
not easily accessible and sometimes buggy (as in the case of the Python
SAGE implementation, which can produce non-optimal solutions), and their
performances have never been compared in public. For PACE, we imposed a
unified input/output format for the challenge and required all
implementations to be made available on github. Moreover, the details
and raw data of all results mentioned in this document can be found in
the github repository
<a href="https://github.com/holgerdell/PACE-treewidth-testbed">https://github.com/holgerdell/PACE-treewidth-testbed</a>
that we published; using the tools and benchmark instances in the
repository, it is a trivial matter to reproduce the results.</p>
<h3 id="submissions">Submissions</h3>
<p>The list of all implementation submissions can be found here:
<a href="https://github.com/holgerdell/PACE-treewidth-testbed/blob/master/pace2016-submissions.yaml">https://github.com/holgerdell/PACE-treewidth-testbed/blob/master/pace2016-submissions.yaml</a></p>
<p>Two people submitted real-world instances:</p>
<ul>
<li>Johannes Fichte (TU Wien) submitted <a href="https://github.com/daajoe/PACE2016_transit_graphs">transit
networks</a>.</li>
<li>Ben Strasser (Karlsruhe Institute of Technology) submitted <a href="https://github.com/ben-strasser/road-graphs-pace16">road
graphs</a>.</li>
</ul>
<h4 id="exact-treewidth">Exact treewidth</h4>
<p>The goal of this challenge was to compute a tree decomposition of
minimum width. Three teams participated in this track, and two PACE
co-organizers contributed a further
implementation.</p>
<p><img src="https://pacechallenge.files.wordpress.com/2016/09/ex.png?w=748" alt="ex.png" /></p>
<p>This plot shows one data point per solver-instance pair. The
x-coordinate corresponds to the treewidth of the instance and the
y-coordinate corresponds to the running time. We aborted the computation
after a timeout of 100 seconds for most instances; some instances had a
timeout of 1000 and 3600 seconds; in total, we used 200 instances in the
exact competition. The instances are samples of <a href="https://github.com/freetdi/named-graphs">named
graphs</a>, <a href="https://github.com/freetdi/CFGs.git">control flow
graphs</a>, and <a href="http://mat.gsia.cmu.edu/COLOR/instances.html">DIMACS graph coloring
instances.</a></p>
<h4 id="results-and-techniques">Results and Techniques</h4>
<ol>
<li>Tamaki (Meiji University) solved 199 instances. The submission is
written in C++ and is based on a modified version of the brute force
approach of Arnborg et al. (1987).
<a href="https://github.com/TCS-Meiji/treewidth-exact">https://github.com/TCS-Meiji/treewidth-exact</a></li>
<li>Bodlaender & Van der Zanden (Utrecht University) solved 173
instances. The submission is written in C# / Mono and relies on
balanced separators as well as dynamic programming.
<a href="https://github.com/TomvdZanden/BZTreewidth">https://github.com/TomvdZanden/BZTreewidth</a></li>
<li>Bannach, Berndt, Ehlers (Luebeck University) solved 166 instances.
The submission is written in Java 8 and relies on a SAT-solver to
find the optimal elimination order.
<a href="https://github.com/maxbannach/Jdrasil">https://github.com/maxbannach/Jdrasil</a></li>
</ol>
<p>The Larisch & Salfelder (Frankfurt University) implementation solved
171 of 200 instances.</p>
<h3 id="heuristic-treewidth">Heuristic treewidth</h3>
<p>The goal of this challenge was to compute a good tree decomposition in
a given fixed timeout. We set the timeout to 100 seconds for every
instance. We used the 200 instances from the exact competition and 81
additional, harder instances from the same sources; arguably, the
instances were generally too easy for the heuristic challenge. Seven
teams participated in this track (9 sequential programs and 3 parallel
programs were submitted). Some teams submitted multiple programs, in
which case we only kept the best-performing submission of each team in
the ranking.</p>
<h4 id="sequential-programs">Sequential programs</h4>
<ol>
<li>Strasser (Karlsruhe Institute of Technology)<br />
<a href="https://github.com/ben-strasser/flow-cutter-pace16">https://github.com/ben-strasser/flow-cutter-pace16</a></li>
<li>Fox-Epstein (Brown University)<br />
<a href="https://github.com/elitheeli/2016-pace-challenge">https://github.com/elitheeli/2016-pace-challenge</a></li>
<li>Abseher, Musliu, Woltran (TU Wien)<br />
<a href="https://github.com/mabseher/htd">https://github.com/mabseher/htd</a></li>
<li>Gaspers, Gudmundsson, Jones, Mestre, Rümmele (UNSW and University of
Sidney)<br />
<a href="https://github.com/mfjones/pace2016">https://github.com/mfjones/pace2016</a></li>
<li>Bannach, Berndt, Ehlers (Luebeck University)<br />
<a href="https://github.com/maxbannach/Jdrasil">https://github.com/maxbannach/Jdrasil</a></li>
<li>Joglekar, Kamble, Pandian (IIT Madras)<br />
<a href="https://github.com/mrprajesh/pacechallenge">https://github.com/mrprajesh/pacechallenge</a></li>
</ol>
<p><img src="https://pacechallenge.files.wordpress.com/2016/09/hesestat.png?w=748" alt="hesestat.png" /></p>
<p>This plot shows, for every sequential submission and every x, the number
y of instances for which the submission computed a tree decomposition of
width at most x. As can be seen, the top three submissions nearly
converge on this metric; this is perhaps explained by the fact that all
three implement the basic MinFill heuristic (tweaked in different ways).
The other three submissions use more interesting techniques from FPT.</p>
<p>For the evaluation, we viewed each instance as a voter and determined
its ranking for the implementations from the width of the tree
decomposition produced by the implementation after 100 seconds. We
combined these votes using the Schulze method. This process can be
inspected in the testbed repository
<a href="https://github.com/holgerdell/PACE-treewidth-testbed/blob/github/logs/2016-08-13.02-08-25/ranks-he-se.txt">https://github.com/holgerdell/PACE-treewidth-testbed/blob/github/logs/2016-08-13.02-08-25/ranks-he-se.txt</a>.</p>
<h4 id="parallel-programs">Parallel programs</h4>
<ol>
<li>Kask, Lam (University of California at Irvine)<br />
<a href="https://github.com/willmlam/CVO2">https://github.com/willmlam/CVO2</a></li>
<li>Strasser (Karlsruhe Institute of Technology)<br />
<a href="https://github.com/ben-strasser/flow-cutter-pace16">https://github.com/ben-strasser/flow-cutter-pace16</a></li>
<li>Bannach, Berndt, Ehlers (Luebeck University)<br />
<a href="https://github.com/maxbannach/Jdrasil">https://github.com/maxbannach/Jdrasil</a></li>
</ol>
<p> </p>
<h2 id="track-b-feedback-vertex-set">Track B: Feedback Vertex Set</h2>
<table>
<tbody>
<tr>
<td>In the <em>Feedback Vertex Set</em> problem we are given an undirected graph and want to compute a smallest vertex set S such that removing S from G results in a forest, that is, a graph without any cycles. Feedback Vertex Set is NP-complete and one of the most prominent problems in parameterized algorithmics. Most fixed-parameter algorithms use the parameter solution size k=</td>
<td>S</td>
<td>.</td>
</tr>
</tbody>
</table>
<p>Virtually all fixed-parameter algorithms make use of the fact that
vertices of degree at most two can be easily removed from the graph.
After this initial removal, a range of different techniques were used in
the fixed-parameter algorithms. The first fixed-parameter algorithm
branches on a shortest cycle in the resulting graph. This cycle has
length O(log n) which results in an overall running time of k^k * poly(n). By using a randomized approach on the resulting graph, a running time of
4^k * poly(n) can be obtained. The first deterministic approaches to achieve running times of the form 2^O(k) * poly(n) use the iterative compression
technique which iteratively builds up the graph by adding one vertex at
a time and makes use of the fact that a size-k solution can be stored during this computation. Other fixed-parameter algorithms for this problem can be obtained by branching on a vertex of maximum degree or by LP-based techniques.</p>
<h3 id="challenge-setup-and-participation">Challenge Setup and Participation</h3>
<p>We collected 230 graphs which were mostly from various application
fields such as social networks, biological networks, road networks,
incidence graphs of CNF-SAT formules. The graphs were selected so that
there was a steady progression from easy to hard instances.</p>
<p>To determine the winners, we counted the number of instances that could
be solved within the given time limit. To avoid overemphasizing
low-level improvements of the algorithms, we set the time limit to 30
minutes per instance. To identify programs that report nonoptimal
solutions we precomputed the optimal solutions for some instances using
an ILP that was given at least 30 minutes on each instance. This ILP is
based on cycle constraints. More precisely, we add constraints enforcing
that for each cycle at least one vertex must be deleted by any solution.
Since the number of constraints is usually exponential, they are added
in a lazy fashion, that is, we compute a solution with only some initial
constraints and check whether the solution is a feedback vertex set. If
this is the case, then we have found an optimal solution, otherwise we
add constraints for some of the remaining cycles and compute a new
solution until a feedback vertex set is
found.</p>
<p>[Overall, 14 teams registered out of which seven eventually submitted a
program. From those teams that submitted a program, three were from
Germany, one from India, one from Japan, one from Poland, and one from
Russia.</p>
<h3 id="challenge-results">Challenge Results</h3>
<p>In the following, we give for each team further details such as the
number of solved instances, a brief algorithm description, the names of
the participants, and a link to the code repository. The entries are
sorted by place in descending order. All submissions apply a reduction
rule that removes all vertices of degree at most two.</p>
<ol>
<li>Yoichi Iwata (NII) and Kensuke Imanishi (University of Tokyo).
This submission solved 84 out of 130 instances. The algorithm
utilizes an LP-based branching and an LP-based kernelization. The
program is written in Java and available at <a href="https://github.com/wata-orz/fvs">https://github.com/wata-orz/fvs</a>.</li>
<li>Marcin Pilipczuk (University of Warsaw). This submission solved 66
out of 130 instances. The algorithm branches on a vertex of maximum
degree. In addition, instances with small treewidth are solved by
dynamic programming on tree decompositions and subcubic instances
are solved by a polynomial-time algorithm that is based on a
reduction to the graphic matroid parity problem. The program is
written in C++ and available at <a href="https://bitbucket.org/marcin_pilipczuk/fvs-pace-challenge">https://bitbucket.org/marcin_pilipczuk/fvs-pace-challenge</a>.</li>
<li>Ruben Becker, Karl Bringmann, Dennis Gross, Erik Jan van Leeuwen,
and Natalie Wirth (MPI Saarbrücken). This
submission solved 50 out of 130 instances. The algorithm also
branches on vertices of the highest degree, the search tree is
pruned by computing upper and lower bounds. The program is written
in C++ and available at <a href="https://github.com/erikjanvl/FVS_MPI">https://github.com/erikjanvl/FVS_MPI</a>.</li>
<li>Niklas Paulsen, Kevin Prohn, Malin Rau, and Lars Rohwedder (Kiel
University). This submission solved 47 out of 130 instances. The
algorithm is based on the combination of iterative compression with
an improved branching strategy. Subcubic graphs are solved again by
reduction graphic matroid parity. The program is written in C# and
available at <a href="https://git.informatik.uni-kiel.de/npau/FFF">https://git.informatik.uni-kiel.de/npau/FFF</a>.</li>
<li>Shivam Garg (IIT Bombay), G. Philip and Apoorva Tamaskar (Chennai
Mathematical Institute). This submission solved 41 out of 130
instances. The algorithm branches on a shortest cycle. This program
is written in Python and available at <a href="https://bitbucket.org/gphilip_bitbucket/pace-code">https://bitbucket.org/gphilip_bitbucket/pace-code</a>.</li>
<li>Fabian Brand, Simon Gehring, Florian Nelles, Kevin Wilkinghoff, and
Xianghui Zhong (University of Bonn). This submission solved 34 out
of 130 instances. The algorithm is based on iterative compression
and also solves subcubic instances in polynomial time. The program
is written in C++ and available at
<a href="https://github.com/s-gehring/feedback-vertex-set">https://github.com/s-gehring/feedback-vertex-set</a>.</li>
<li>Svyatoslav Feldsherov (Moscow State University). This submission
solved 22 out of 130 instances. The alg orithm uses the randomized
approach with running time 4^k n^O(1).
An improvement is gained for the case where two vertices are
connected by a multiedge. In this case, the algorithm branches
directly on these two vertices. The program is written in C++ and
available at <a href="https://github.com/feldsherov/pace2016">https://github.com/feldsherov/pace2016</a>.</li>
</ol>
<p>As a final remark, the ILP solved 81 out of 130 instances. Thus, the
best FPT approaches were competitive with this particular ILP
formulation. Since better ILP formulations are possible, a more thorough
comparison with further ILP-based approaches would be necessary to gain
insight into the relative performance of FPT-based and ILP-based
approaches for Feedback Vertex Set.</p>PACE ChallengeThe winners of the 1st PACE competition were presented at ALGO 2016 in Aarhus. For those that couldn’t make it to Aarhus: here are the results. We would like to thank all participants for making this 1st edition of PACE an enjoyable and successful one.Challenge Prizes and Travel Awards2016-06-22T00:00:00+00:002016-06-22T00:00:00+00:00https://pacechallenge.org/2016/06/22/prizes-and-awards<p>Thanks to the generous support of the NWO Gravitation project <a href="http://thenetworkcenter.nl/">NETWORKS</a>, we can announce the following awards for the first PACE challenge.</p>
<h2 id="competition-prizes">Competition Prizes</h2>
<p>For each of the two tracks we award prizes. Track A offers four ranked challenges: exact sequential, exact parallel, heuristic sequential, and heuristic parallel computation of treewidth. For each ranked challenge, there will be a first, second, and third prize.</p>
<ul>
<li>Each first prize will receive 200 €.</li>
<li>Each second prize will receive 100 €.</li>
<li>Each third prize will receive 75 €.</li>
</ul>
<p>Track B offers one ranked challenge and there will be altogether three prizes for this challenge.</p>
<ul>
<li>The first prize will receive 500 €.</li>
<li>The second prize will receive 300 €.</li>
<li>The third prize will receive 200 €.</li>
</ul>
<p>The ranking criteria for each challenge are described in the description of each track.</p>
<h2 id="travel-awards">Travel Awards</h2>
<p>With these awards, we aim to encourage young researchers to attend <a href="http://conferences.au.dk/algo16/ipec/">IPEC</a> and <a href="http://conferences.au.dk/algo16/algo-frontpage/">ALGO</a>. Altogether, three travel awards of 500 € will be handed out. To apply for a travel award send an e-mail including a CV and a motivation letter to Frances Rosamond, Chair of the Steering Committee, University of Bergen. The application deadline is July 20, 2016. To be eligible one must</p>
<ul>
<li>submit a working implementation in one of the PACE challenges,</li>
<li>be a full-time student (undergraduate or graduate level, excluding
PhD students), and</li>
<li>give a commitment to attend <a href="http://conferences.au.dk/algo16/ipec/">IPEC</a> in case one receives the award.</li>
</ul>PACE ChallengeThanks to the generous support of the NWO Gravitation project NETWORKS, we can announce the following awards for the first PACE challenge.The First PACE Challenge2016-03-01T00:00:00+00:002016-03-01T00:00:00+00:00https://pacechallenge.org/2016/03/01/the-first-PACE<p>The goal of the Parameterized Algorithms and Computational Experiments Challenge (PACE) is to investigate the applicability of algorithmic ideas studied and developed in the subfields of multivariate, fine-grained, parameterized, or fixed-parameter tractable algorithms. In particular, it aims to</p>
<ul>
<li>provide a bridge between the theory of design and analysis of algorithms and the algorithm engineering practice,</li>
<li>inspire new theoretical developments,</li>
<li>investigate the competitiveness of analytical and design frameworks developed in the communities,</li>
<li>produce universally accessible libraries of implementations and repositories of benchmark instances, and</li>
<li>encourage the dissemination of these findings in scientific papers.</li>
</ul>
<p>The challenge will feature two tracks, Track A deals with the Tree Width Problem, and Track B deals with the Feedback Vertex Set Problem. The tracks have different aims: Track A has a broad scope including the call for algorithms that may solve the problem heuristically and for generators of hard instances. Track B aims for fixed-parameter algorithms that need to solve the Feedback Vertex Set problem exactly and has a fixed evaluation criterion. Therefore, Track B will have one or more winners that will be announced at IPEC 2016.</p>
<p>For each track, participation in the challenge essentially means submitting a program for the respective problem. During the algorithm development, the programs can be tested on a data set provided by the track chairs.</p>
<p>Due to the different aims of the two tracks, the technical requirements for submission differ somewhat. Moreover, since this is the first implementation challenge in parameterized algorithms, experimenting with different competition modes and submission formats may give valuable hints for future challenges.</p>PACE ChallengeThe goal of the Parameterized Algorithms and Computational Experiments Challenge (PACE) is to investigate the applicability of algorithmic ideas studied and developed in the subfields of multivariate, fine-grained, parameterized, or fixed-parameter tractable algorithms. In particular, it aims to