Difference between revisions of "Optimization Group Meetings"

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You can subscribe to an [http://en.wikipedia.org/wiki/ICalendar iCalendar] of these meetings at http://iridia.ulb.ac.be/Calendars/publish.php/_NUC_Optimization.ics
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==Purpose==
  
   
  +
==Breakfast Meetings==
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The goal of the optimization weekly meeting is to facilitate and support the development and conduct of research in optimization at IRIDIA. The meeting will help you in your efforts to develop research ideas, gives feedback on your work and serves as a means for disseminating your research results.
  
   
  +
===Purpose===
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# '''Community'''. Keep everyone updated as to what other work in optimization is going on in the lab.
  
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# '''Research'''. Share research results. Discussions of general interest. Literature study on specific topics. Inspiration for new research. Reports on conference visits.
  
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# '''Admin'''. Optimization group administration. Discussion of practical problems. Guidelines for software etc.
 
   
  +
Breakfast meetings are informal meetings where there is a general discussion or someone presents their work. And additional goal is to have breakfast together.
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<br>
  
   
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==Format==
  
   
  +
=== Organization ===
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# Presentation & Discussion (30 - 50 mins)
  
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#* Work you have been doing
  
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#* Reading you have been doing in the context of your work
  
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#* Other reading on something you are passionate about
  
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# Optimization group administration (0 - 30 mins)
  
   
  +
# Send an email to the [[Lab_responsibilities#Seminars_and_meetings | responsible of Optimization Meetings]]. Mention your name, your affiliation, the date, time and room, and a short summary of what you are going to talk about.
  +
# Add a new entry to the table below.
  +
# Bring breakfast.
   
−
Try and make your session as involving as possible for everyone:
  
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* Send the article/handout to be read beforehand.
  
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* Ask people before the meeting what aspects of your work / reading they would like to know about or discuss.
  
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* Think about implications of what you are presenting for the research direction of the lab as a whole - methodologies, technologies etc.
  
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<br>
  
   
  +
=== History of Breakfast Meetings ===
−
==Timing & Attendance==
  
   
  +
{| class="sortable" border="1" cellpadding="2" cellspacing="0"
−
The weekly meetings '''ALWAYS''' (yet to be finalized) take place on
  
  +
|- align="left"
  +
!width="100"|Date
  +
!width="200"|Presenter
  +
!class="unsortable"|Summary
  +
|-
  +
|2014-04-10
  +
|G. Sena DAÅž
  +
| Developing a Solution Algorithm for the Multi-objective Gate Assignment Problems
  +
|-
  +
|2013-09-12
  +
|Leslie Perez
  +
| Tuning and irace
  +
|-
  +
|2011-03-10
  +
|Stefanie Kritzinger
  +
| A Unified Framework for Routing Problems with Fixed Fleet Size
  +
|-
  +
|2010-12-21
  +
|Paola Pellegrini
  +
| Off-line vs. On-line Tuning: A Study on MAX-MIN Ant System for the TSP
  +
|-
  +
|2010-10-19
  +
|Stefano Benedettini
  +
| Experiments on Boolean Network Design by Local Search Algorithms.
  +
|-
  +
|2010-05-20
  +
|Marco Montes de Oca
  +
| The social learning strategies tournament, organized as part of the [http://www.intercult.su.se/cultaptation/ cultaptation project], and its results were described. No ideas about algorithm portfolios were discussed.
  +
|-
  +
|2010-05-??
  +
|Renaud Lenne
  +
| ???
   
  +
|-
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<center> '''Thursdays at 11.00 AM''' </center>
  
  +
|2010-04-29
  +
|Franco Mascia
  +
|The maximum clique problem, state of the art and ACO [http://dx.doi.org/10.1016/j.cor.2009.02.013] [http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.80.2036&rep=rep1&type=pdf] [http://www710.univ-lyon1.fr/~csolnon/publications/rr-mai04.pdf]
   
  +
|-
−
Unless:
  
  +
|2010-03-18
−
* A given Thursday is a public holiday, or
  
  +
|Sabrina Oliveira
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* Something very important (like a Ph.D. defense) is overlapping.
  
  +
|Achieved results from the application of the Population Based Ant Colony Optimisation algorithm to TSP.
  +
|-
  +
|2010-02-11
  +
|Sara Ceschia
  +
|An overview of Container Loading Problems.
  +
|-
  +
| 2010-01-21
  +
|Yuan, Zhi (Eric)
  +
| Rice cooker vs. the idea of tuning.
  +
|-
  +
|2010-01-07
  +
|Thomas Stüztle
  +
|General discussion about the optimization group.
  +
|}
   
  +
==Literature Sessions==
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If either should happen the meeting is postponed to the next day.
  
   
  +
===Purpose===
−
'''Please indicate on this wiki page if you are not going to be able to attend a meeting''' (no later than the Friday before).
 
   
  +
The goal of the Literature Sessions is to examine and discuss
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If you forget to note your absence in advance you will be severely punished and will be forced to buy a nice, big cake (yet to be finalized) for the following meeting.
  
  +
particularly interesting papers from the research literature. For each
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<br><br>
  
  +
session, one paper will be selected, there will be a short
  +
presentation (10-15 minutes) about the contents, and a discussion will
  +
ensue. Sessions will last around 40-45 minutes. Attendants should read
  +
the paper before the session in order to have a productive discussion.
   
−
==Friday 28th October - Prasanna BALAPRAKASH==
  
   
  +
=== Organization ===
−
'''''Agenda'''''
  
−
# '''Short Introduction to the optimization group weekly meeting'''
  
−
# '''Presentation / Discussion'''
  
−
#* Local Search under Uncertainty
  
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#* Probabilistic Traveling Salesman Problem as a case study
  
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#* Overview of the state-of-the-art local search techniques to tackle uncertainty
  
−
#* Empirical estimation based local search to tackle uncertainty
  
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# '''Optimization Group Admin'''
  
−
#* Structure for the weekly meeting
  
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#* Time schedule for the Optimization weekly meeting
  
−
#* Wiki page administration
  
−
#* Next week...
  
   
  +
# Send an email to the [[Lab_responsibilities#Seminars_and_meetings | responsible of Optimization Meetings]]. Mention your name, your affiliation, the date, time and room, a reference to the paper and the URL where it can be obtained. Also, attach the paper in PDF.
−
'''''People who will be absent'''''
  
  +
# Add a new entry to the table below. Use YYY-MM-DD (year-month-day) format for the date. Please add a complete bibliographic reference (you may find it in the homepages of the authors) and a hyperlink to a PDF (links to http://dx.doi.org are preferred).
−
<br>
  
−
-NA-
  
   
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'''''Results'''''
  
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* Sharing Code: Writing code in a way such that others can understand (with comments where ever possible). This helps to share the code with others.
  
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* For the moment, the weekly meeting is scheduled on Thursdays at 11.00 AM.
 
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* The person, who is giving the talk, should present the field/area in which he/she considers himself/herself as an expert for about 5 mins.
 
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* We should agree on the coding language and compilers('''if possible'''). At the moment we are using Mauro's R "code" for statistical analysis and parameter tuning. This code will be made available in this wiki.
 
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* Skripts for doing useful things will be collected and also be made available in this wiki.
  
   
  +
=== History of Literature Sessions ===
   
  +
{| class="sortable" border="1" cellpadding="2" cellspacing="0"
  +
|- align="left"
  +
!width="100"|Date
  +
!width="180"|Presenter
  +
!class="unsortable"|Paper discussed
  +
|-
  +
|2015-01-09
  +
| Alberto Franzin
  +
|Chris Fawcett, Holger H. Hoos. 2015. Analysing differences between algorithm configurations through ablation. In Journal of Heuristics, 2015. http://dx.doi.org/10.1007/s10732-014-9275-9
   
−
[[Media :EmpiricalLocalSearch.pdf|Download Presentation(PDF)]]
  
   
  +
Frank Hutter, Holger Hoos, Kevin Leyton-Brown. 2014. An efficient approach for assessing Hyperparameter importance. In Proceedings of the 31st International Conference of Machine Learning (ICML), 2014. http://jmlr.org/proceedings/papers/v32/hutter14.pdf
  +
|-
  +
|2014-10-07
  +
| Leslie Perez
  +
|Martin Zaefferer, Jörg Stork, Martina Friese, Andreas Fischbach, Boris Naujoks, and Thomas Bartz-Beielstein. 2014. Efficient global optimization for combinatorial problems. In Proceedings of the 2014 conference on Genetic and evolutionary computation (GECCO), 2014. http://doi.acm.org/10.1145/2576768.2598282
   
  +
Martin Zaefferer, Jörg Stork, Thomas Bartz-Beielstein: Distance Measures for Permutations in Combinatorial Efficient Global Optimization. PPSN 2014. http://doi.acm.org/10.1145/2576768.2598260
−
<br>
  
  +
|-
  +
|2014-02-20
  +
| Thomas Stutzle
  +
|A unified solution framework for multi-attribute vehicle routing problems.
  +
Thibaut Vidal, Teodor Gabriel Crainic, Michel Gendreau, and Christian Prins.
  +
http://dx.doi.org/10.1016/j.ejor.2013.09.045
  +
|-
  +
|2013-10-03
  +
|Leonardo Bezerra
  +
|Robust Benchmark Set Selection for Boolean Constraint Solvers. Holger Hoos, Benjamin Kaufmann, Torsten Schaub and Marius Schneider - Proceedings of the 7th International Conference on Learning and Intelligent Optimization (LION 7), to appear, 2013. http://www.cs.ubc.ca/~hoos/Publ/HooEtAl13-preprint.pdf
   
  +
Quantifying Homogeneity of Instance Sets for Algorithm Configuration. Marius Schneider and Holger H. Hoos - Proceedings of the 6th International Conference on Learning and Intelligent Optimization (LION 6), pp. 190-204, 2012. http://www.cs.ubc.ca/~hoos/Publ/SchHoo12.pdf
−
==Thursday 3nd November - Max MANFRIN==
  
  +
|-
  +
|2013-09-12
  +
|Manuel López-Ibáñez
  +
|Automated Parameter Tuning Framework for Heterogeneous and Large Instances: Case study in Quadratic Assignment Problem Lindawati, Zhi Yuan, Hoong Chuin Lau & Feida Zhu. http://lion.disi.unitn.it/intelligent-optimization//LION7/Lindawati-Yuan-Lau-Zhu_Automated%20Parameter%20Tuning.pdf
  +
|-
  +
|2013-04-11
  +
|Leslie Perez
  +
| C. Ansótegui, M. Sellmann, and K. Tierney, “A Gender-Based Genetic Algorithm for the Automatic Configuration of Algorithms,” in Principles and Practice of Constraint Programming - CP 2009, I. P. Gent, Ed. Springer Berlin Heidelberg, 2009, pp. 142–157. http://itu.dk/people/kevt/papers/gga-cp2009.pdf
  +
|-
  +
|2012-10-18
  +
|Manuel López-Ibáñez
  +
| Yuri Malitsky, Meinolf Sellmann: Instance-Specific Algorithm Configuration as a Method for Non-Model-Based Portfolio Generation. CPAIOR 2012: 244-259
  +
http://dx.doi.org/10.1007/978-3-642-29828-8_16
  +
|-
  +
|2012-10-12
  +
| Tianjun Liao
  +
|Bernd Bischl, Olaf Mersmann, Heike Trautmann, and Mike Preuß. 2012. Algorithm selection based on exploratory landscape analysis and cost-sensitive learning. In Proceedings of the fourteenth international conference on Genetic and evolutionary computation conference (GECCO 2012), Terence Soule (Ed.). ACM, New York, NY, USA, 313-320. DOI:[http://doi.acm.org/10.1145/2330163.2330209 10.1145/2330163.2330209]
   
  +
Olaf Mersmann, Bernd Bischl, Heike Trautmann, Mike Preuss, Claus Weihs, and Günter Rudolph. 2011. Exploratory landscape analysis. In
  +
Proceedings of the 13th annual conference on Genetic and evolutionary computation (GECCO 2011), Natalio Krasnogor (Ed.). ACM, New York, NY, USA, 829-836. DOI:[http://doi.acm.org/10.1145/2001576.2001690 10.1145/2001576.2001690]
  +
|-
  +
|2012-04-19
  +
|Franco Mascia
  +
|E.K. Burke, M.R. Hyde, and G. Kendall. Grammatical Evolution of Local Search Heuristics. IEEE Transactions on Evolutionary Computation, 99, 2011. doi: 10.1109/TEVC.2011.2160401 [http://www.cs.nott.ac.uk/~mvh/papers/mvh-draft-ieeetec2011.pdf PDF]
  +
|-
  +
|2012-04-03
  +
|[http://iridia.ulb.ac.be/~jdubois/ Jérémie Dubois-Lacoste]
  +
|On the automatic discovery of variants of the NEH procedure for flow shop scheduling using genetic programming. J A Vázquez-Rodríguez and G Ochoa.Journal of the Operational Research Society (2011) 62, 381–396. doi:[http://dx.doi.org/10.1057/jors.2010.132 10.1057/jors.2010.132]
  +
|-
  +
|2011-12-08
  +
|Zhi Yuan
  +
|Frank Hutter, Holger Hoos, and Kevin Leyton-Brown. Sequential Model-Based Optimization for General Algorithm Configuration. In Proceedings of Learning and Intelligent Optimization (LION 5), 2011. PDF: [http://www.cs.ubc.ca/~hutter/papers/11-LION5-SMAC.pdf]
  +
|-
  +
|2011-11-24
  +
|Manuel López-Ibáñez
  +
|Ender Özcan and Andrew J. Parkes. 2011. Policy matrix evolution for generation of heuristics. In Proceedings of the 13th annual conference on Genetic and evolutionary computation (GECCO 2011), Natalio Krasnogor (Ed.). ACM, New York, NY, USA, 2011-2018. DOI: [http://dx.doi.org/10.1145/2001576.2001846 10.1145/2001576.2001846]
  +
|-
  +
|2011-02-04
  +
|Paola Pellegrini
  +
|HAL: A Framework for the Automated Analysis and Design of High-Performance Algorithms. By Christopher Nell, Chris Fawcett, Holger H. Hoos, and Kevin Leyton-Brown. [http://hal.cs.ubc.ca/pubs/NelEtAl11.pdf PDF]
  +
|-
  +
|2010-12-17
  +
|Marco Montes de Oca
  +
|A. LaTorre, S. Muelas, and J.-M. Peña. A MOS-based dynamic memetic differential evolution algorithm for continuous optimization: a scalability test. Soft Computing. Special issue on Scalability of Evolutionary Algorithms and other Metaheuristics for Large Scale Continuous Optimization Problems. DOI [http://dx.doi.org/10.1007/s00500-010-0646-3 10.1007/s00500-010-0646-3]
  +
|-
  +
|2010-11-10
  +
|[http://iridia.ulb.ac.be/~manuel/ Manuel López-Ibáñez]
  +
|A Rigorous Analysis of the Harmony Search Algorithm--How the Research Community can be misled by a "novel" Methodology. Dennis Weyland. International Journal of Applied Metaheuristic Computing, volume 1-2, April-June 2010, pages 50-60. DOI: [http://dx.doi.org/10.4018/jamc.2010040104 10.4018/jamc.2010040104]
   
  +
Survival of the Fittest Algorithm or the Novelest Algorithm?: The Existence Reason of the Harmony Search Algorithm. Zong Woo Geem.
−
'''''Agenda'''''
  
   
  +
|-
−
# '''Introduction / General interest discussion'''
  
  +
|2010-09-23
−
#* Brief introduction on Max background
  
  +
|Gianpiero Francesca
−
#* IRIDIA Cluster
 
  +
|Wenyin Gong, Álvaro Fialho and Zhihua Cai. Adaptive Strategy Selection in Differential Evolution. In J. Branke et al., eds.: "GECCO'10: Proc. 12th Annual Conference on Genetic and Evolutionary Computation", ACM Press : p. 409-416. July 2010. [http://hal.archives-ouvertes.fr/docs/00/47/12/68/PDF/AOS-DE.pdf]
−
#** [http://iridia.ulb.ac.be/~alyhne/wiki/index.php/IRIDIA_cluster_architecture The architecture of the IRIDIA cluster]
  
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#** The Sun Grid Engine queueing system
  
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#** [http://iridia.ulb.ac.be/~alyhne/wiki/index.php/Using_the_IRIDIA_Cluster Policies for submission and execution of the jobs]
  
−
# '''Presentation / Discussion'''
  
−
#* Survey on Parallelization of Ant Colony Optimization
  
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#* Proposal of a parallel design for ACO algorithm to solve Rich Vehicle Routing Problems
  
   
  +
Álvaro Fialho, Marc Schoenauer and Michele Sebag. Toward Comparison-based Adaptive Operator Selection. In J. Branke et al., eds.: "GECCO'10: Proc. 12th Annual Conference on Genetic and Evolutionary Computation", ACM Press : p. 767-774. July 2010. [http://hal.archives-ouvertes.fr/docs/00/47/12/64/PDF/banditGECCO10.pdf]
   
  +
|-
−
'''''Linked Presentations'''''
  
  +
|2010-06-03
  +
|Tianjun Liao
  +
|Population-Based Algorithm Portfolios for Numerical Optimization. Peng, F. Tang, K.Chen, G.Yao, X. IEEE Transactions on Evolutionary Computation. DOI: [http://dx.doi.org/10.1109/TEVC.2010.2040183 10.1109/TEVC.2010.2040183]
   
  +
|-
−
* [http://landau.ulb.ac.be/~mmanfrin/media/pdf/MPI-overview.pdf An overview on Parallel Computing and Message Passing] Seminar at IRDIA - ULB, Brussels, Belgium, January 26, 2005
  
  +
|2010-05-07
  +
|Zhi (Eric) Yuan
  +
|Hydra: Automatically Configuring Algorithms for Portfolio-Based Selection. L. Xu, H.H. Hoos, K. Leyton-Brown. To appear at the Conference of the Association for the Advancement of Artificial Intelligence (AAAI-10), 2010. [http://ws.cs.ubc.ca/~kevinlb/pub.php?u=2010-AAAI-Hydra.pdf]
   
  +
|-
  +
|2010-03-04
  +
|Sara Ceschia
  +
|A. Schaerf and L. Di Gaspero. [[:Image:ElPaCo_presentation.pdf|Slides of the tutorial "An Overview of Local Search Software Tools"]] given at "Learning and Intelligent OptimizatioN (LION 2007)", December 8-12, 2007, Trento, Italy.
   
  +
L. Di Gaspero and A. Schaerf. EASY LOCAL++: An object-oriented framework for flexible design of local search algorithms. Software — Practice & Experience, 33(8):733–765, July 2003. [http://www.diegm.uniud.it/satt/papers/DiSc03.pdf]
−
'''''Reading Material'''''
  
   
  +
S. Cahon, N. Melab and T. El Ghazali. ParadisEO: A Framework for the Reusable Design of Parallel and Distributed Metaheuristics. Journal of Heuristics, 10(3):357-380, November 2004. [http://dx.doi.org/10.1023/B:HEUR.0000026900.92269.ec]
−
* There is no reading material for this weeks presentation
  
   
  +
|-
  +
|2010-02-19
  +
|Sabrina M. de Oliveira
  +
|A study on the use of non-parametric tests for analyzing the evolutionary algorithms' behaviour: a case study on the CEC'2005 Session on Real Parameter Optimization. S. Garcia, D. Molina, M. Lozano, F. Herrera - Journal of Heuristics, Volume 15, pp. 617-644, 2009. [http://sci2s.ugr.es/programacion/workshop/GarciaMolinaLozanoHerrera-JH2008.pdf]
   
  +
|-
−
'''''People who will be absent'''''
  
  +
|2010-02-04
  +
|Thomas Stüztle
  +
|Analyzing Bandit-based Adaptive Operator Selection Mechanisms. Álvaro Fialho, Luis Da Costa, Marc Schoenauer and Michéle Sebag.
   
  +
|-
−
Christophe Philemotte
  
  +
|2010-01-14
−  
  +
|[http://iridia.ulb.ac.be/~jdubois/ Jérémie Dubois-Lacoste]
−
<br><br>
  
  +
|SATzilla: Portfolio-based Algorithm Selection for SAT. L. Xu, F. Hutter, H. H. Hoos, K. Leyton-Brown - Journal of Artificial Intelligence Research, Volume 32, pp. 565-606, 2008. [http://www.jair.org/media/2490/live-2490-3923-jair.pdf]
−  
  +
|-
−
==Wednesday 9th November - Jodelson A. SABINO==
  
  +
|2009-12-11
−  
  +
|[http://iridia.ulb.ac.be/~manuel/ Manuel López-Ibáñez]
−
This talk is going to be given as a IRIDIA seminar. Therefore it will not take place on Thursday but on Wednesday. After the talk, there will be a MEETOPT discussion about the organizational matters.
  
  +
|SATenstein: Automatically Building Local Search SAT Solvers From Components. Ashiqur R. KhudaBukhsh, Lin Xu, Holger H. Hoos and Kevin Leyton-Brown - Proceedings of the 21st International Joint Conference on Artificial Intelligence (IJCAI-09), pp. 517-524, 2009. [http://www.cs.ubc.ca/labs/beta/Projects/SATenstein/SATenstein_ijcai.pdf]
−  
  +
|}
−
'''''Agenda'''''
  
−  
−
# '''Introduction'''
  
−
#* Field of expertise etc.
  
−
# '''Presentation / Discussion'''
  
−
#* The Problem of Railroad Yards Operational Planning
  
−
# '''MEETOPT Admin (10-15 mins)'''
  
−  
−  
−
'''''Linked Presentations'''''
  
−  
−
'''''Abstract and Reading Material'''''
  
−  
−
* [http://iridia.ulb.ac.be/seminars/index.php?x=00070 The Problem of Railroad Yards Operational Planning]
  
−  
−
'''''People who will be absent'''''
  
 
<br>
  
<br>
−
Christophe Philemotte
 
−  
−
<br><br>
  
−  
−
==Thursday 17th November - Jodelson A. SABINO==
  
−  
−
'''''Agenda'''''
  
−  
−
# '''Introduction'''
  
−
# '''Presentation / Discussion'''
  
−
#* A certain solution for the Switch Engine Assignment Problem
  
−
# '''MEETOPT Admin (10-15 mins)'''
  
−  
−  
−
'''''Linked Presentations'''''
  
−  
−
'''''Abstract and Reading Material'''''
  
−  
−
This seminar gives an overview of the algorithm presented in Jodelson's Master
  
−
Degree dissertation to solve the Switch Engine Assignment Problem. This presentation
 
−
start with a quick review of the problem statement (as it was presented in a previous
 
−
IRIDIA seminar), definition of the concept of PDP path and the solution by the RR-COMPETants
 
−
algorithm.
  
−  
−
* [http://iridia.ulb.ac.be/seminars/index.php?x=00070 The Problem of Railroad Yards Operational Planning]
  
−  
−
'''''People who will be absent'''''
  
 
<br>
  
<br>
−
N.A.
  
   
  +
== Other Previous Meetings==
−
<br><br>
  
   
  +
See [[Previous Optimization meetings | Minutes and agendas from previous meetings]].
−
==Thursday 24th November - Thomas STÜTZLE==
  
−  
−
'''''Agenda'''''
  
−  
−
# '''Introduction'''
  
−
# '''Presentation / Discussion'''
  
−
#* Stochastic Local Search, introduction and engineering of algorithms
  
−
# '''MEETOPT Admin (10-15 mins)'''
  
−  
−  
−
'''''Linked Presentations'''''
  
−  
−
'''''Abstract and Reading Material'''''<br>
  
−
This presentation explaines concisely what Stochastic Local Search is and gives some thoughts on further work in this area that should lead to what can be called "Stochastic Local Search algorithms Engineering" or, short, SLS Engineering. <br>
  
−  
−
[[Media :ORP3.2005.pdf|Download Presentation(PDF)]]
  
−  
−
'''''People who will be absent'''''
  
−
<br>
  
−
N.A.
  
−  
−
<br><br>
  
−  
−
==Wednsday 30th November - Marco MONTES DE OCA==
  
−  
−
'''''Agenda'''''
  
−  
−
# '''Introduction'''
  
−
# '''Presentation / Discussion'''
  
−
#* Particle Swarm Optimization
  
−
# '''MEETOPT Admin (10-15 mins)'''
  
−  
−  
−
'''''Linked Presentations'''''
  
−  
−
[[Media :Slides.pdf|Download Presentation(PDF)]]
  
−  
−  
−
'''''Abstract and Reading Material'''''
  
−  
−
Particle Swarm Optimization (PSO for short) was first inspired by the flocking behavior of birds, although it also has roots in some theories of social adaptation.
  
−
PSO is a population-based optimization technique in which each individual or "particle" represents a solution to a continuous optimization problem. Associated
  
−
with each particle, there is a velocity vector that changes according to its own best past performance and that of its neighbors. In this way, particles "fly"
  
−
over the search space resembling the movement of insects in a swarm.
  
−  
−
After its first publication, PSO has attracted the interest of a growing research community because it is conceptually simple, technically easy to implement,
 
−
and has been successfully applied to many problems.
  
−  
−
In this meeting, a brief overview of what has been done in PSO research and possible future work will be presented.
  
−  
−
[http://www.swarmintelligence.org/tutorials.php PSO introductory tutorial]
  
−  
−
'''''People who will be absent'''''
  
−
<br>
  
−
N.A.
  
−  
−
<br><br>
  
−  
−  
−  
−
==Thursday 8th December - Andrea ROLI==
  
−  
−
'''''Agenda'''''
  
−  
−
# '''Introduction'''
  
−
# '''Presentation / Discussion'''
  
−
#* An introduction to constraint programming (for metaheuristic-minded researchers) -- Part 1
  
−  
−
'''''Abstract and Reading Material'''''<br>
  
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[http://iridia.ulb.ac.be/seminars/index.php?x=00072 Click here for more details]
  
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[[Media :Roli Talk Dec.4perpage.pdf|Download Presentation(PDF)]]
  
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'''''People who will be absent'''''
  
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<br>
  
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Marco DORIGO, Thomas STÜTZLE
  
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<br><br>
  
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==Friday 9th December - Andrea ROLI==
  
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'''''Agenda'''''
  
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# '''Introduction'''
  
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# '''Presentation / Discussion'''
  
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#* An introduction to constraint programming (for metaheuristic-minded researchers) -- Part 2
  
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'''''Abstract and Reading Material'''''<br>
  
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[http://iridia.ulb.ac.be/seminars/index.php?x=00073 Click here for more details]
  
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'''''People who will be absent'''''
  
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<br>
  
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Marco DORIGO, Thomas STÜTZLE
  
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<br><br>
  
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==Thursday 12th January - Tom LENAERTS==
  
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'''''Agenda'''''
  
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# '''Introduction'''
  
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# '''Presentation / Discussion'''
  
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#* Evolutionary Transitions in Solution Complexity
  
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'''''Abstract'''''<br>
  
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Recently, Evolutionary Biology has proposed a generalised theory for the origin of complexity in biological systems. This theory, referred to as Evolutionary Transition Theory, provides a description on how complexity could have arisen out of the interaction of simple components. A well-known example is the transition from single cell to multi-cellularity. As evolution itself, this theory provides a metaphor for optimisation and learning where complex solutions are constructed through the evolutionary combination of partial ones. This talk discusses a new evolutionary algorithm based on this metaphor. We show that, in the context of constraint satisfaction problems, this metaphor provides a very useful technique to find solutions. Moreover, the results of this basic, unoptimised algorithm are close to what is observed in other highly-adjusted evolutionary techniques. As a consequence, it provides an important foundation for the further investigation of compositional algorithms in the context of optimisation
  
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'''''People who will be absent'''''
  
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<br>
  
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<br><br>
  
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==Thursday 19th January - General Discussion (Optimization Library)==
  
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'''''Agenda'''''
  
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# '''Outcome of the discussion'''
  
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#*The C programming language will be selected for the implementation and development. We'll follow the C99 standard and use GCC compiler tools ([http://gcc.gnu.org/c99status.html Status of C99 features in GCC]). The standard compiler is the one provided in the most recent stable version of Debian.
  
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#**[http://www.kuro5hin.org/story/2001/2/23/194544/139 Are you Ready For C99?]
 
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#**[http://www-128.ibm.com/developerworks/linux/library/l-c99.html?ca=dgr-lnxw07UsingC99 Open source development using C99]
  
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#* We will have a look at [http://www.gnu.org/prep/standards/standards.pdf GNU coding standards] and if everyone feels it is good then they will be adopted.
  
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#*[http://subversion.tigris.org/ Subversion] will be adopted as the revision control system (Max will make a brief study)
 
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#*The format of result files should be standardised (Mauro, Thomas and Prasanna will come up with a format which should be discussed later).
  
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#*Common scripts have to be developed to extract required information from the results file should be developed. Mauro, Thomas, and Prasanna make an initial list of scripts to be developped.
  
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#*Mauro will have a look at COMET software libraries book and Prasanna will check about software libraries, in general, and the features they provide.
 
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#**Short term goal - sharing code to save the development time
  
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#**Long term goal - IRIDIA Optimization Library
  
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<br><br>
  
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==Thursday 26th January - Thomas STÜTZLE==
  
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'''''Agenda'''''
  
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# '''Introduction'''
  
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# '''Presentation / Discussion'''
  
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#* Empirical analysis of stochastic algorithms by measuring run-time distributions
  
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# '''MEETOPT Admin (10-15 mins)'''
  
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#* Follow-up of the meeting about optimization libraries, tools etc. of the previous week
  
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'''''Linked Presentations'''''
  
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'''''Abstract and Reading Material'''''<br>
  
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We start now the part of presentations / discussions on specific topics. The first topic to be discussed in a number of presentations / discussions is the '''Empirical Analysis of Algorithms, in particular SLS Algorithms'''. In this series we will discuss methods for their empirical analysis including run-time distributions, statistical analysis (hypothesis tests, ANOVA and alike methods), experimental design, tuning of algorithms, etc. We start this series by a presentation about the empirical analysis of algorithms through measuring run-time distributions. The presentation will be based on Chapter 4 of the book about ''Stochastic Local Search: Foundations and Applications'' by Holger Hoos and Thomas. The slides for the presentation are available via [http://wwww.sls-book.net SLS:FA] (check for the slides and figures section). The presentation will discuss only a small selection of the most important issues presented there.<br>
  
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'''''People who will be absent'''''
  
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<br>
  
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N.A.
  
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<br><br>
  

Latest revision as of 17:01, 8 January 2015

You can subscribe to an iCalendar of these meetings at http://iridia.ulb.ac.be/Calendars/publish.php/_NUC_Optimization.ics

Breakfast Meetings

Purpose

Breakfast meetings are informal meetings where there is a general discussion or someone presents their work. And additional goal is to have breakfast together.


Organization

  1. Send an email to the responsible of Optimization Meetings. Mention your name, your affiliation, the date, time and room, and a short summary of what you are going to talk about.
  2. Add a new entry to the table below.
  3. Bring breakfast.


History of Breakfast Meetings

Date Presenter Summary
2014-04-10 G. Sena DAÅž Developing a Solution Algorithm for the Multi-objective Gate Assignment Problems
2013-09-12 Leslie Perez Tuning and irace
2011-03-10 Stefanie Kritzinger A Unified Framework for Routing Problems with Fixed Fleet Size
2010-12-21 Paola Pellegrini Off-line vs. On-line Tuning: A Study on MAX-MIN Ant System for the TSP
2010-10-19 Stefano Benedettini Experiments on Boolean Network Design by Local Search Algorithms.
2010-05-20 Marco Montes de Oca The social learning strategies tournament, organized as part of the cultaptation project, and its results were described. No ideas about algorithm portfolios were discussed.
2010-05-?? Renaud Lenne ???
2010-04-29 Franco Mascia The maximum clique problem, state of the art and ACO [1] [2] [3]
2010-03-18 Sabrina Oliveira Achieved results from the application of the Population Based Ant Colony Optimisation algorithm to TSP.
2010-02-11 Sara Ceschia An overview of Container Loading Problems.
2010-01-21 Yuan, Zhi (Eric) Rice cooker vs. the idea of tuning.
2010-01-07 Thomas Stüztle General discussion about the optimization group.

Literature Sessions

Purpose

The goal of the Literature Sessions is to examine and discuss particularly interesting papers from the research literature. For each session, one paper will be selected, there will be a short presentation (10-15 minutes) about the contents, and a discussion will ensue. Sessions will last around 40-45 minutes. Attendants should read the paper before the session in order to have a productive discussion.


Organization

  1. Send an email to the responsible of Optimization Meetings. Mention your name, your affiliation, the date, time and room, a reference to the paper and the URL where it can be obtained. Also, attach the paper in PDF.
  2. Add a new entry to the table below. Use YYY-MM-DD (year-month-day) format for the date. Please add a complete bibliographic reference (you may find it in the homepages of the authors) and a hyperlink to a PDF (links to http://dx.doi.org are preferred).


History of Literature Sessions

Date Presenter Paper discussed
2015-01-09 Alberto Franzin Chris Fawcett, Holger H. Hoos. 2015. Analysing differences between algorithm configurations through ablation. In Journal of Heuristics, 2015. http://dx.doi.org/10.1007/s10732-014-9275-9


Frank Hutter, Holger Hoos, Kevin Leyton-Brown. 2014. An efficient approach for assessing Hyperparameter importance. In Proceedings of the 31st International Conference of Machine Learning (ICML), 2014. http://jmlr.org/proceedings/papers/v32/hutter14.pdf

2014-10-07 Leslie Perez Martin Zaefferer, Jörg Stork, Martina Friese, Andreas Fischbach, Boris Naujoks, and Thomas Bartz-Beielstein. 2014. Efficient global optimization for combinatorial problems. In Proceedings of the 2014 conference on Genetic and evolutionary computation (GECCO), 2014. http://doi.acm.org/10.1145/2576768.2598282

Martin Zaefferer, Jörg Stork, Thomas Bartz-Beielstein: Distance Measures for Permutations in Combinatorial Efficient Global Optimization. PPSN 2014. http://doi.acm.org/10.1145/2576768.2598260

2014-02-20 Thomas Stutzle A unified solution framework for multi-attribute vehicle routing problems.

Thibaut Vidal, Teodor Gabriel Crainic, Michel Gendreau, and Christian Prins. http://dx.doi.org/10.1016/j.ejor.2013.09.045

2013-10-03 Leonardo Bezerra Robust Benchmark Set Selection for Boolean Constraint Solvers. Holger Hoos, Benjamin Kaufmann, Torsten Schaub and Marius Schneider - Proceedings of the 7th International Conference on Learning and Intelligent Optimization (LION 7), to appear, 2013. http://www.cs.ubc.ca/~hoos/Publ/HooEtAl13-preprint.pdf

Quantifying Homogeneity of Instance Sets for Algorithm Configuration. Marius Schneider and Holger H. Hoos - Proceedings of the 6th International Conference on Learning and Intelligent Optimization (LION 6), pp. 190-204, 2012. http://www.cs.ubc.ca/~hoos/Publ/SchHoo12.pdf

2013-09-12 Manuel López-Ibáñez Automated Parameter Tuning Framework for Heterogeneous and Large Instances: Case study in Quadratic Assignment Problem Lindawati, Zhi Yuan, Hoong Chuin Lau & Feida Zhu. http://lion.disi.unitn.it/intelligent-optimization//LION7/Lindawati-Yuan-Lau-Zhu_Automated%20Parameter%20Tuning.pdf
2013-04-11 Leslie Perez C. Ansótegui, M. Sellmann, and K. Tierney, “A Gender-Based Genetic Algorithm for the Automatic Configuration of Algorithms,” in Principles and Practice of Constraint Programming - CP 2009, I. P. Gent, Ed. Springer Berlin Heidelberg, 2009, pp. 142–157. http://itu.dk/people/kevt/papers/gga-cp2009.pdf
2012-10-18 Manuel López-Ibáñez Yuri Malitsky, Meinolf Sellmann: Instance-Specific Algorithm Configuration as a Method for Non-Model-Based Portfolio Generation. CPAIOR 2012: 244-259

http://dx.doi.org/10.1007/978-3-642-29828-8_16

2012-10-12 Tianjun Liao Bernd Bischl, Olaf Mersmann, Heike Trautmann, and Mike Preuß. 2012. Algorithm selection based on exploratory landscape analysis and cost-sensitive learning. In Proceedings of the fourteenth international conference on Genetic and evolutionary computation conference (GECCO 2012), Terence Soule (Ed.). ACM, New York, NY, USA, 313-320. DOI:10.1145/2330163.2330209

Olaf Mersmann, Bernd Bischl, Heike Trautmann, Mike Preuss, Claus Weihs, and Günter Rudolph. 2011. Exploratory landscape analysis. In Proceedings of the 13th annual conference on Genetic and evolutionary computation (GECCO 2011), Natalio Krasnogor (Ed.). ACM, New York, NY, USA, 829-836. DOI:10.1145/2001576.2001690

2012-04-19 Franco Mascia E.K. Burke, M.R. Hyde, and G. Kendall. Grammatical Evolution of Local Search Heuristics. IEEE Transactions on Evolutionary Computation, 99, 2011. doi: 10.1109/TEVC.2011.2160401 PDF
2012-04-03 Jérémie Dubois-Lacoste On the automatic discovery of variants of the NEH procedure for flow shop scheduling using genetic programming. J A Vázquez-Rodríguez and G Ochoa.Journal of the Operational Research Society (2011) 62, 381–396. doi:10.1057/jors.2010.132
2011-12-08 Zhi Yuan Frank Hutter, Holger Hoos, and Kevin Leyton-Brown. Sequential Model-Based Optimization for General Algorithm Configuration. In Proceedings of Learning and Intelligent Optimization (LION 5), 2011. PDF: [4]
2011-11-24 Manuel López-Ibáñez Ender Özcan and Andrew J. Parkes. 2011. Policy matrix evolution for generation of heuristics. In Proceedings of the 13th annual conference on Genetic and evolutionary computation (GECCO 2011), Natalio Krasnogor (Ed.). ACM, New York, NY, USA, 2011-2018. DOI: 10.1145/2001576.2001846
2011-02-04 Paola Pellegrini HAL: A Framework for the Automated Analysis and Design of High-Performance Algorithms. By Christopher Nell, Chris Fawcett, Holger H. Hoos, and Kevin Leyton-Brown. PDF
2010-12-17 Marco Montes de Oca A. LaTorre, S. Muelas, and J.-M. Peña. A MOS-based dynamic memetic differential evolution algorithm for continuous optimization: a scalability test. Soft Computing. Special issue on Scalability of Evolutionary Algorithms and other Metaheuristics for Large Scale Continuous Optimization Problems. DOI 10.1007/s00500-010-0646-3
2010-11-10 Manuel López-Ibáñez A Rigorous Analysis of the Harmony Search Algorithm--How the Research Community can be misled by a "novel" Methodology. Dennis Weyland. International Journal of Applied Metaheuristic Computing, volume 1-2, April-June 2010, pages 50-60. DOI: 10.4018/jamc.2010040104

Survival of the Fittest Algorithm or the Novelest Algorithm?: The Existence Reason of the Harmony Search Algorithm. Zong Woo Geem.

2010-09-23 Gianpiero Francesca Wenyin Gong, Álvaro Fialho and Zhihua Cai. Adaptive Strategy Selection in Differential Evolution. In J. Branke et al., eds.: "GECCO'10: Proc. 12th Annual Conference on Genetic and Evolutionary Computation", ACM Press : p. 409-416. July 2010. [5]

Álvaro Fialho, Marc Schoenauer and Michele Sebag. Toward Comparison-based Adaptive Operator Selection. In J. Branke et al., eds.: "GECCO'10: Proc. 12th Annual Conference on Genetic and Evolutionary Computation", ACM Press : p. 767-774. July 2010. [6]

2010-06-03 Tianjun Liao Population-Based Algorithm Portfolios for Numerical Optimization. Peng, F. Tang, K.Chen, G.Yao, X. IEEE Transactions on Evolutionary Computation. DOI: 10.1109/TEVC.2010.2040183
2010-05-07 Zhi (Eric) Yuan Hydra: Automatically Configuring Algorithms for Portfolio-Based Selection. L. Xu, H.H. Hoos, K. Leyton-Brown. To appear at the Conference of the Association for the Advancement of Artificial Intelligence (AAAI-10), 2010. [7]
2010-03-04 Sara Ceschia A. Schaerf and L. Di Gaspero. Slides of the tutorial "An Overview of Local Search Software Tools" given at "Learning and Intelligent OptimizatioN (LION 2007)", December 8-12, 2007, Trento, Italy.

L. Di Gaspero and A. Schaerf. EASY LOCAL++: An object-oriented framework for flexible design of local search algorithms. Software — Practice & Experience, 33(8):733–765, July 2003. [8]

S. Cahon, N. Melab and T. El Ghazali. ParadisEO: A Framework for the Reusable Design of Parallel and Distributed Metaheuristics. Journal of Heuristics, 10(3):357-380, November 2004. [9]

2010-02-19 Sabrina M. de Oliveira A study on the use of non-parametric tests for analyzing the evolutionary algorithms' behaviour: a case study on the CEC'2005 Session on Real Parameter Optimization. S. Garcia, D. Molina, M. Lozano, F. Herrera - Journal of Heuristics, Volume 15, pp. 617-644, 2009. [10]
2010-02-04 Thomas Stüztle Analyzing Bandit-based Adaptive Operator Selection Mechanisms. Álvaro Fialho, Luis Da Costa, Marc Schoenauer and Michéle Sebag.
2010-01-14 Jérémie Dubois-Lacoste SATzilla: Portfolio-based Algorithm Selection for SAT. L. Xu, F. Hutter, H. H. Hoos, K. Leyton-Brown - Journal of Artificial Intelligence Research, Volume 32, pp. 565-606, 2008. [11]
2009-12-11 Manuel López-Ibáñez SATenstein: Automatically Building Local Search SAT Solvers From Components. Ashiqur R. KhudaBukhsh, Lin Xu, Holger H. Hoos and Kevin Leyton-Brown - Proceedings of the 21st International Joint Conference on Artificial Intelligence (IJCAI-09), pp. 517-524, 2009. [12]



Other Previous Meetings

See Minutes and agendas from previous meetings.

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