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teaching:mfe:ia [2014/05/13 17:21] mdorigo |
teaching:mfe:ia [2014/10/14 13:59] stuetzle [Comparison of fast heuristics for the longest common subsequence problem] |
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| * Contacts : [[http://iridia.ulb.ac.be/~mdorigo/HomePageDorigo/ | Marco Dorigo]] and Dhananjay Ipparthi (IRIDIA) | * Contacts : [[http://iridia.ulb.ac.be/~mdorigo/HomePageDorigo/ | Marco Dorigo]] and Dhananjay Ipparthi (IRIDIA) | ||
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| - | ===== Simulation et optimisation de trafic routier ===== | ||
| - | |||
| - | Mentis, spin-off du laboratoire IRIDIA, est une société de consultance | ||
| - | spécialisée en Data Mining et en Text Mining. Mentis cherche | ||
| - | actuellement des mémorants pour lancer diverses études d’optimisation | ||
| - | dans le domaine de la simulation de trafic routier. | ||
| - | |||
| - | Dans le cadre d’un projet pour un de ses clients, Mentis travaille | ||
| - | actuellement dans le domaine de la simulation de trafic routier. | ||
| - | L’objectif du mémoire proposé consiste à lancer plusieurs études | ||
| - | d’optimisation pour évaluer l’impact de différentes politiques | ||
| - | routières sur le trafic. Il sera demandé à l’étudiant de mettre en | ||
| - | œuvre diverses techniques d’optimisation afin de déterminer les | ||
| - | politiques routières optimales. Une grande partie du mémoire sera | ||
| - | faite dans les bureaux de Mentis ainsi qu’en interaction directe avec | ||
| - | le client. | ||
| - | |||
| - | |||
| - | * Contacts: | ||
| - | * [[psener@mentis-consulting.be|Pierre Sener (Mentis)]] | ||
| - | * [[http://code.ulb.ac.be/iridia.people.php?id=1|Hugues Bersini (IRIDIA)]] | ||
| - | * [[http://iridia.ulb.ac.be/~stuetzle/|Thomas Stützle (IRIDIA)]] | ||
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| * [[http://code.ulb.ac.be/iridia.people.php?id=1|Hugues Bersini (IRIDIA)]] | * [[http://code.ulb.ac.be/iridia.people.php?id=1|Hugues Bersini (IRIDIA)]] | ||
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| - | ===== Comparison of fast heuristics for the longest common subsequence problem ===== | ||
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| - | The [[http://en.wikipedia.org/wiki/Longest_common_subsequence|longest common subsequence (LCS) problem]] has important applications in Computational Biology. Several heuristic methods have been proposed to obtain approximate solutions. These methods require different computation time and obtain solutions of varied quality. In this project, the student will learn several methods that have been proposed in the literature to tackle a difficult optimization problem, and compare them in terms of computation time and quality of the resulting solutions. The final goal is to propose appropriate combinations of existing methods that solve diverse instances of the LCS problem. | ||
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| - | * Contacts : | ||
| - | * [[http://iridia.ulb.ac.be/~manuel|Manuel López-Ibáñez (IRIDIA)]] | ||
| - | * [[http://iridia.ulb.ac.be/~stuetzle|Thomas Stützle (IRIDIA)]] | ||