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Academic Training Lecture Regular Programme
Evolutionary Heuristic Optimization: Genetic Algorithms and Estimation of Distribution Algorithms (4/4)
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Europe/Zurich
500/1-001 - Main Auditorium (CERN)
Description
In the real world, there exist a huge number of problems that require getting an optimum or near-to-optimum solution. Optimization can be used to solve a lot of different problems such as network design, sets and partitions, storage and retrieval or scheduling.
On the other hand, in nature, there exist many processes that seek a stable state. These processes can be seen as natural optimization processes. Over the last 30 years several attempts have been made to develop optimization algorithms, which simulate these natural processes. These attempts have resulted in methods such as Simulated Annealing, based on natural annealing processes or Evolutionary Computation, based on biological evolution processes.
Genetic Algorithms and Estimation of Distribution Algorithms are successful strategies that belong to the Evolutionary Computation Field.
