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teaching:mfe:ia [2015/04/11 17:36] stuetzle [Graphical Tools for analysing Multi-Objective Data.] |
teaching:mfe:ia [2015/04/11 17:44] stuetzle [Applications of the Multi-objective ACO framework] |
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| * [[http://iridia.ulb.ac.be/~stuetzle|Thomas Stützle (IRIDIA)]] | * [[http://iridia.ulb.ac.be/~stuetzle|Thomas Stützle (IRIDIA)]] | ||
| * [[http://iridia.ulb.ac.be/~mbiro|Mauro Birattari (IRIDIA)]] | * [[http://iridia.ulb.ac.be/~mbiro|Mauro Birattari (IRIDIA)]] | ||
| - | * [[http://iridia.ulb.ac.be/~manuel|Manuel López-Ibáñez (IRIDIA)]] | + | * [[http://iridia.ulb.ac.be/~lperez|Leslie Perez (IRIDIA)]] |
| - | * [[http://iridia.ulb.ac.be/~jdubois|Jérémie Dubois-Lacoste (IRIDIA)]] | + | |
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| * [[http://iridia.ulb.ac.be/~fmascia|Franco Mascia (IRIDIA)]] | * [[http://iridia.ulb.ac.be/~fmascia|Franco Mascia (IRIDIA)]] | ||
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| - | ===== Analysis of Local Optima Networks for the Max-Clique problem. ====== | ||
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| - | Stochastic Local Search algorithms search for optimal solutions in a large space of candidate solutions. Local Optima Networks (LON) are representations of search landscapes of combinatorial optimisation problems. In these networks, nodes are local optima of the problem, and edges are weighted transitions between the optima. These networks model in a more compact way the properties of the larger search spaces they represent. | ||
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| - | The goal of this project is to build LON of small instances of the Maximum Clique (MC) problem, and measure properties that could illustrate the differences between instance families. | ||
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| - | The MC problem is an NP-hard combinatorial optimisation problem that asks to find the biggest completely connected component of a graph. It has relevant applications in information retrieval, computer vision, social network analysis, computational biochemistry, bioinformatics and genomics. | ||
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| - | Required skills: good knowledge of C or C++ programming. | ||
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| - | * Contacts : | ||
| - | * [[http://iridia.ulb.ac.be/~stuetzle|Thomas Stützle (IRIDIA)]] | ||
| - | * [[http://iridia.ulb.ac.be/~fmascia|Franco Mascia (IRIDIA)]] | ||
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| * Contacts : | * Contacts : | ||
| * [[http://iridia.ulb.ac.be/~stuetzle|Thomas Stützle (IRIDIA)]] | * [[http://iridia.ulb.ac.be/~stuetzle|Thomas Stützle (IRIDIA)]] | ||
| - | * [[http://iridia.ulb.ac.be/~fmascia|Franco Mascia (IRIDIA)]] | ||
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| - | ===== Applications of the Multi-objective ACO framework ===== | + | ===== Applications of a hybrid SLS algorithm framework ===== |
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| - | We have recently developed a software framework of Ant Colony Optimization algorithms for multi-objective optimization problems. This framework has only been applied to a few problems. The goal of this project would be to extend this framework to other problems and compare its results with the methods proposed in the literature. The student will learn to solve multi-objective optimization problems with ACO algorithms, automatic configuration of optimization algorithms, and analysis and comparison of optimization algorithms for multi-objective problems. | + | |
| - | + | ||
| - | * Contacts : | + | |
| - | * [[http://iridia.ulb.ac.be/~manuel|Manuel López-Ibáñez (IRIDIA)]] | + | |
| - | * [[http://iridia.ulb.ac.be/~stuetzle|Thomas Stützle (IRIDIA)]] | + | |
| - | * [[http://iridia.ulb.ac.be/~mdorigo|Marco Dorigo (IRIDIA)]] | + | |
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| - | ===== A graphical interface for the optimisation of Water Distribution Networks ===== | + | |
| - | The [[http://iridia.ulb.ac.be/~manuel/doc/cec2005-presentation.pdf|optimization of the operations of Water Distribution Networks]] may save important amounts of energy and its associated costs, and, therefore, it is an important problem in practice. There are [[http://www.epa.gov/nrmrl/wswrd/dw/epanet.html|graphical tools and simulators]] available. In addition, several optimization methods based on [[http://iridia.ulb.ac.be/~manuel/doc/cec2005.pdf|evolutionary algorithms]] and [[http://dx.doi.org/10.1061/(ASCE)0733-9496(2008)134:4(337)|ant colony optimization]] have been proposed in the literature. The goal of this project is to integrate the optimization algorithms into a graphical environment that can be used by water engineers and operators. No knowledge about water distribution networks is necessary. The optimisation algorithms and toolkit libraries for handling water distribution networks will be available to the student. | + | We have recently developed a software framework from which hybrid stochastic local search algorithms can be designed automatically. This framework has only been applied to a few problems. The goal of this project would be to extend this framework to other problems and compare its results with the methods proposed in the literature. The student will learn to solve combinatorial optimization problems with SLS algorithms, automatic configuration of optimization algorithms, and analysis and comparison of optimization algorithms. |
| * Contacts : | * Contacts : | ||
| - | * [[http://iridia.ulb.ac.be/~manuel|Manuel López-Ibáñez (IRIDIA)]] | ||
| * [[http://iridia.ulb.ac.be/~stuetzle|Thomas Stützle (IRIDIA)]] | * [[http://iridia.ulb.ac.be/~stuetzle|Thomas Stützle (IRIDIA)]] | ||
| + | * [[http://code.ulb.ac.be/iridia.people.php?id=1388|Federico Pagnozzi (IRIDIA)]] | ||