Optimization Group Meetings

Purpose

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.

1. Community. Keep everyone updated as to what other work in optimization is going on in the lab.
2. Research. Share research results. Discussions of general interest. Literature study on specific topics. Inspiration for new research. Reports on conference visits.
3. Admin. Optimization group administration. Discussion of practical problems. Guidelines for software etc.

Format

1. Presentation & Discussion (30 - 50 mins)
   • Work you have been doing
   • Reading you have been doing in the context of your work
   • Other reading on something you are passionate about
2. Optimization group administration (0 - 30 mins)

Try and make your session as involving as possible for everyone:

• Send the article/handout to be read beforehand.
• Ask people before the meeting what aspects of your work / reading they would like to know about or discuss.
• Think about implications of what you are presenting for the research direction of the lab as a whole - methodologies, technologies etc.

Timing & Attendance

The weekly meetings ALWAYS (yet to be finalized) take place on

Thursdays at 11.00 AM

Unless:

• A given Thursday is a public holiday, or
• Something very important (like a Ph.D. defense) is overlapping.

If either should happen the meeting is postponed to the next day.

Please indicate on this wiki page if you are not going to be able to attend a meeting (no later than the Friday before).

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.

Friday 28th October - Prasanna BALAPRAKASH

Agenda

1. Short Introduction to the optimization group weekly meeting
2. Presentation / Discussion
   • Local Search under Uncertainty
   • Probabilistic Traveling Salesman Problem as a case study
   • Overview of the state-of-the-art local search techniques to tackle uncertainty
   • Empirical estimation based local search to tackle uncertainty
3. Optimization Group Admin
   • Structure for the weekly meeting
   • Time schedule for the Optimization weekly meeting
   • Wiki page administration
   • Next week...

People who will be absent
-NA-

Results

• 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.
• For the moment, the weekly meeting is scheduled on Thursdays at 11.00 AM.
• 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.
• 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.
• Skripts for doing useful things will be collected and also be made available in this wiki.

Download Presentation(PDF)

Thursday 3nd November - Max MANFRIN

Agenda

1. Introduction / General interest discussion
   • Brief introduction on Max background
   • IRIDIA Cluster
     • The architecture of the IRIDIA cluster
     • The Sun Grid Engine queueing system
     • Policies for submission and execution of the jobs
2. Presentation / Discussion
   • Survey on Parallelization of Ant Colony Optimization
   • Proposal of a parallel design for ACO algorithm to solve Rich Vehicle Routing Problems

Linked Presentations

• An overview on Parallel Computing and Message Passing Seminar at IRDIA - ULB, Brussels, Belgium, January 26, 2005

Reading Material

• There is no reading material for this weeks presentation

People who will be absent

Christophe Philemotte

Wednesday 9th November - Jodelson A. SABINO

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.

Agenda

1. Introduction
   • Field of expertise etc.
2. Presentation / Discussion
   • The Problem of Railroad Yards Operational Planning
3. MEETOPT Admin (10-15 mins)

Linked Presentations

Abstract and Reading Material

• The Problem of Railroad Yards Operational Planning

People who will be absent
Christophe Philemotte

Thursday 17th November - Jodelson A. SABINO

Agenda

1. Introduction
2. Presentation / Discussion
   • A certain solution for the Switch Engine Assignment Problem
3. 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.

• The Problem of Railroad Yards Operational Planning

People who will be absent
N.A.

Thursday 24th November - Thomas STÜTZLE

Agenda

1. Introduction
2. Presentation / Discussion
   • Stochastic Local Search, introduction and engineering of algorithms
3. MEETOPT Admin (10-15 mins)

Linked Presentations

Abstract and Reading Material
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.

Download Presentation(PDF)

People who will be absent
N.A.

Wednsday 30th November - Marco MONTES DE OCA

Agenda

1. Introduction
2. Presentation / Discussion
   • Particle Swarm Optimization
3. MEETOPT Admin (10-15 mins)

Linked Presentations

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.

PSO introductory tutorial

People who will be absent
N.A.

Thursday 8th December - Andrea ROLI

Agenda

1. Introduction
2. Presentation / Discussion
   • An introduction to constraint programming (for metaheuristic-minded researchers) -- Part 1

Abstract and Reading Material
Click here for more details

Download Presentation(PDF)

People who will be absent
Marco DORIGO, Thomas STÜTZLE

Friday 9th December - Andrea ROLI

Agenda

1. Introduction
2. Presentation / Discussion
   • An introduction to constraint programming (for metaheuristic-minded researchers) -- Part 2

Abstract and Reading Material
Click here for more details

People who will be absent
Marco DORIGO, Thomas STÜTZLE

Thursday 12th January - Tom LENAERTS

Agenda

1. Introduction
2. Presentation / Discussion
   • Evolutionary Transitions in Solution Complexity

Abstract
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

People who will be absent

Thursday 19th January - General Discussion (Optimization Library)

Agenda

1. Outcome of the discussion
   • The C programming language will be selected for the implementation and development. We'll follow the C99 standard and use GCC compiler tools (Status of C99 features in GCC). The standard compiler is the one provided in the most recent stable version of Debian.
     • Are you Ready For C99?
     • Open source development using C99
   • We will have a look at GNU coding standards and if everyone feels it is good then they will be adopted.
   • Subversion will be adopted as the revision control system (Max will make a brief study)
   • The format of result files should be standardised (Mauro, Thomas and Prasanna will come up with a format which should be discussed later).
   • 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.
   • Mauro will have a look at COMET software libraries book and Prasanna will check about software libraries, in general, and the features they provide.
     • Short term goal - sharing code to save the development time
     • Long term goal - IRIDIA Optimization Library
   • Christophe suggests Doxygen as documentation tools.

Thursday 26th January - Thomas STÜTZLE

Agenda

1. Introduction
2. Presentation / Discussion
   • Empirical analysis of stochastic algorithms by measuring run-time distributions
3. MEETOPT Admin (10-15 mins)
   • Follow-up of the meeting about optimization libraries, tools etc. of the previous week

Linked Presentations

Abstract and Reading Material
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 SLS:FA (check for the slides and figures section). The presentation will discuss only a small selection of the most important issues presented there.

People who will be absent
N.A.