This shows you the differences between two versions of the page.
| Both sides previous revision Previous revision Next revision | Previous revision Next revision Both sides next revision | ||
|
teaching:mfe:ia [2017/04/20 18:29] stuetzle [Automatic configuration of hybrid algorithms] |
teaching:mfe:ia [2017/04/20 18:33] stuetzle |
||
|---|---|---|---|
| Line 211: | Line 211: | ||
| - | ===== Software framework for Ant Colony Optimization ===== | + | ===== Software framework for ant colony optimization ===== |
| Ants have inspired a number of computational techniques and among the most successful is ant colony optimization (ACO). ACO is an optimization technique that can be applied to tackle a wide variety of computational problems that arise in computer science, telecommunications, and engineering. While ACO has a very wide applicability, the development times for effective ACO algorithms can be relatively high. This is due to the fact that each time a new problem is to be tackled by an ACO algorithm, a researcher needs to implement the algorithms almost from scratch. | Ants have inspired a number of computational techniques and among the most successful is ant colony optimization (ACO). ACO is an optimization technique that can be applied to tackle a wide variety of computational problems that arise in computer science, telecommunications, and engineering. While ACO has a very wide applicability, the development times for effective ACO algorithms can be relatively high. This is due to the fact that each time a new problem is to be tackled by an ACO algorithm, a researcher needs to implement the algorithms almost from scratch. | ||
| Line 218: | Line 218: | ||
| The application of this software framework will be tested on a number of optimization problems. | The application of this software framework will be tested on a number of optimization problems. | ||
| - | Required skills: The candidate should be well acquainted with programming in object oriented languages. | + | Required skills: The candidate should be well acquainted with programming in object oriented languages. |
| + | |||
| + | |||
| + | * Contacts : | ||
| + | * [[http://iridia.ulb.ac.be/~mdorigo|Marco Dorigo (IRIDIA)]] | ||
| + | * [[http://iridia.ulb.ac.be/~stuetzle|Thomas Stützle (IRIDIA)]] | ||
| + | |||
| + | |||
| + | |||
| + | ===== Software framework for ant colony optimization ===== | ||
| + | |||
| + | Ants have inspired a number of computational techniques and among the most successful is ant colony optimization (ACO). ACO is an optimization technique that can be applied to tackle a wide variety of computational problems that arise in computer science, telecommunications, and engineering. While ACO has a very wide applicability, the development times for effective ACO algorithms can be relatively high. This is due to the fact that each time a new problem is to be tackled by an ACO algorithm, a researcher needs to implement the algorithms almost from scratch. | ||
| + | |||
| + | The goal of the project is to provide a software framework to support the application and the implementation of ACO algorithms to new problems. The software framework will offer all the standard procedures that are used in ACO algorithms and will allow for the rapid prototyping of ACO algorithms. | ||
| + | The application of this software framework will be tested on a number of optimization problems. | ||
| + | |||
| + | Required skills: The candidate should be well acquainted with programming in object oriented languages. | ||